Tongliang Liu - RankMe

622 papers A* 190A 5B 2C 2Journal 403Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bifrost: Steering Strategic Trajectories to Bridge Contextual Gaps for Self-Improving Agents. CoRR Quan M. Tran, Zhuo Huang, Wenbin Zhang, Bo Han, Koji Yatani, Masashi Sugiyama, Tongliang Liu
2026	J	`jnl`	BrokenBind: Universal Modality Exploration beyond Dataset Boundaries. CoRR Zhuo Huang, Runnan Chen, Bo Han, Gang Niu, Masashi Sugiyama, Tongliang Liu
2026	J	`jnl`	C-WOE: Clustering for Out-of-Distribution Detection Learning With Wild Outlier Exposure. IEEE Trans. Image Process. Long Lan, Zhaohui Hu, He Li, Tongliang Liu, Xinwang Liu
2026	J	`jnl`	CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad. CoRR Yongqiang Chen, Chenxi Liu, Zhenhao Chen, Tongliang Liu, Bo Han, Kun Zhang
2026	J	`jnl`	Combating Noisy Labels through Fostering Self- and Neighbor-Consistency. CoRR Zeren Sun, Yazhou Yao, Tongliang Liu, Zechao Li, Fumin Shen, Jinhui Tang
2026	J	`jnl`	Cross-domain Few-shot Classification via Invariant-content Feature Reconstruction. Int. J. Comput. Vis. Hongduan Tian, Feng Liu, Ka Chun Cheung, Zhen Fang, Simon See, Tongliang Liu, Bo Han
2026	J	`jnl`	Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning. Trans. Mach. Learn. Res. Ali Taheri Ghahrizjani, Alireza Taban, Qizhou Wang, Shanshan Ye, Abdolreza Mirzaei, Tongliang Liu, Bo Han
2026	A*	`conf`	GUIC: Certified Graph Unlearning with Individual Fairness Guarantees. AAAI Zichong Wang, Tongliang Liu, Wenbin Zhang
2026	J	`jnl`	HUGE-Bench: A Benchmark for High-Level UAV Vision-Language-Action Tasks. CoRR Jingyu Guo, Ziye Chen, Ziwen Li, Zhengqing Gao, Jiaxin Huang, Hanlue Zhang, Fengming Huang, Yu Yao, Tongliang Liu, Mingming Gong
2026	J	`jnl`	Hierarchical Collaborative Fusion for 3D Instance-aware Referring Expression Segmentation. CoRR Keshen Zhou, Runnan Chen, Mingming Gong, Tongliang Liu
2026	J	`jnl`	Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey. CoRR Longjie Zhao, Ziming Hong, Jiaxin Huang, Runnan Chen, Mingming Gong, Tongliang Liu
2026	J	`jnl`	Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning. CoRR Zhuo Huang, Qizhou Wang, Ziming Hong, Shanshan Ye, Bo Han, Tongliang Liu
2026	J	`jnl`	Jo-SNC: Combating Noisy Labels Through Fostering Self- and Neighbor-Consistency. IEEE Trans. Pattern Anal. Mach. Intell. Zeren Sun, Yazhou Yao, Tongliang Liu, Zechao Li, Fumin Shen, Jinhui Tang
2026	J	`jnl`	KineVLA: Towards Kinematics-Aware Vision-Language-Action Models with Bi-Level Action Decomposition. CoRR Gaoge Han, Zhengqing Gao, Ziwen Li, Jiaxin Huang, Shaoli Huang, Fakhri Karray, Mingming Gong, Tongliang Liu
2026	A*	`conf`	La La LiDAR: Large-Scale Layout Generation from LiDAR Data. AAAI Youquan Liu, Lingdong Kong, Weidong Yang, Xin Li, Alan Liang, Runnan Chen, Ben Fei, Tongliang Liu
2026	J	`jnl`	LightHarmony3D: Harmonizing Illumination and Shadows for Object Insertion in 3D Gaussian Splatting. CoRR Tianyu Huang, Zhenyang Ren, Zhenchen Wan, Jiyang Zheng, Wenjie Wang, Runnan Chen, Mingming Gong, Tongliang Liu
2026	J	`jnl`	MeGU: Machine-Guided Unlearning with Target Feature Disentanglement. CoRR Haoyu Wang, Zhuo Huang, Xiaolong Wang, Bo Han, Zhiwei Lin, Tongliang Liu
2026	J	`jnl`	Mirage2Matter: A Physically Grounded Gaussian World Model from Video. CoRR Zhengqing Gao, Ziwen Li, Xin Wang, Jiaxin Huang, Zhenyang Ren, Mingkai Shao, Hanlue Zhang, Tianyu Huang, Yongkang Cheng, Yandong Guo, Runqi Lin, Yuanyuan Wang, Tongliang Liu, Kun Zhang, Mingming Gong
2026	J	`jnl`	Mitigating Mismatch within Reference-based Preference Optimization. CoRR Suqin Yuan, Xingrui Yu, Jiyang Zheng, Lei Feng, Dadong Wang, Ivor W. Tsang, Tongliang Liu
2026	J	`jnl`	Mobile-VTON: High-Fidelity On-Device Virtual Try-On. CoRR Zhenchen Wan, Ce Chen, Runqi Lin, Jiaxin Huang, Tianxi Chen, Yanwu Xu, Tongliang Liu, Mingming Gong
2026	J	`jnl`	NVS-SQA: Exploring Self-Supervised Quality Representation Learning for Neurally Synthesized Scenes Without References. IEEE Trans. Pattern Anal. Mach. Intell. Qiang Qu, Yiran Shen, Xiaoming Chen, Yuk Ying Chung, Weidong Cai, Tongliang Liu
2026	J	`jnl`	OneWorld: Taming Scene Generation with 3D Unified Representation Autoencoder. CoRR Sensen Gao, Zhaoqing Wang, Qihang Cao, Dongdong Yu, Changhu Wang, Tongliang Liu, Mingming Gong, Jiawang Bian
2026	J	`jnl`	Privacy-Preserving Model Transcription with Differentially Private Synthetic Distillation. CoRR Bochao Liu, Shiming Ge, Pengju Wang, Shikun Li, Tongliang Liu
2026	J	`jnl`	Release the Potential of Memory Buffer in Continual Learning: A Dynamic System Perspective. IEEE Trans. Pattern Anal. Mach. Intell. Zhenyi Wang, Li Shen, Tiehang Duan, Yanjun Zhu, Tongliang Liu, Mingchen Gao, Dacheng Tao
2026	J	`jnl`	Rethinking Deep Research from the Perspective of Web Content Distribution Matching. CoRR Zixuan Yu, Zhenheng Tang, Tongliang Liu, Chengqi Zhang, Xiaowen Chu, Bo Han
2026	A*	`conf`	Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer. AAAI Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu
2026	J	`jnl`	Slack Federated Adversarial Training. IEEE Trans. Pattern Anal. Mach. Intell. Jianing Zhu, Bo Han, Jiangchao Yao, Quanming Yao, Tongliang Liu, Jianliang Xu
2026	J	`jnl`	Unifying Stable Optimization and Reference Regularization in RLHF. CoRR Li He, Qiang Qu, He Zhao, Stephen Wan, Dadong Wang, Lina Yao, Tongliang Liu
2026	J	`jnl`	Unsupervised Synthetic Image Attribution: Alignment and Disentanglement. CoRR Zongfang Liu, Guangyi Chen, Boyang Sun, Tongliang Liu, Kun Zhang
2026	J	`jnl`	VII: Visual Instruction Injection for Jailbreaking Image-to-Video Generation Models. CoRR Bowen Zheng, Yongli Xiang, Ziming Hong, Zerong Lin, Chaojian Yu, Tongliang Liu, Xinge You
2026	J	`jnl`	When Safety Collides: Resolving Multi-Category Harmful Conflicts in Text-to-Image Diffusion via Adaptive Safety Guidance. CoRR Yongli Xiang, Ziming Hong, Zhaoqing Wang, Xiangyu Zhao, Bo Han, Tongliang Liu
2026	J	`jnl`	i-PhysGaussian: Implicit Physical Simulation for 3D Gaussian Splatting. CoRR Yicheng Cao, Zhuo Huang, Yu Yao, Yiming Ying, Daoyi Dong, Tongliang Liu
2025	J	`jnl`	A Knowledge-Guided Adversarial Defense for Resisting Malicious Visual Manipulation. IEEE Trans. Dependable Secur. Comput. Dawei Zhou, Zhigang Su, Decheng Liu, Tongliang Liu, Nannan Wang, Xinbo Gao
2025	J	`jnl`	A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation. CoRR Dawei Zhou, Suzhi Gang, Decheng Liu, Tongliang Liu, Nannan Wang, Xinbo Gao
2025	A*	`conf`	A Lens into Interpretable Transformer Mistakes via Semantic Dependency. ICML Ruo-Jing Dong, Yu Yao, Bo Han, Tongliang Liu
2025	A*	`conf`	A Robust Method to Discover Causal or Anticausal Relation. ICLR Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu
2025	A*	`conf`	A Sample Efficient Conditional Independence Test in the Presence of Discretization. ICML Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang
2025	J	`jnl`	A Sample Efficient Conditional Independence Test in the Presence of Discretization. CoRR Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu, Yumou Qiu, Kun Zhang
2025	J	`jnl`	AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing. CoRR Ziming Hong, Tianyu Huang, Runnan Chen, Shanshan Ye, Mingming Gong, Bo Han, Tongliang Liu
2025	J	`jnl`	Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems. CoRR Bang Liu, Xinfeng Li, Jiayi Zhang, Jinlin Wang, Tanjin He, Sirui Hong, Hongzhang Liu, Shaokun Zhang, Kaitao Song, Kunlun Zhu, Yuheng Cheng, Suyuchen Wang, Xiaoqiang Wang, Yuyu Luo, Haibo Jin, Peiyan Zhang, Ollie Liu, Jiaqi Chen, Huan Zhang, Zhaoyang Yu, Haochen Shi, Boyan Li, Dekun Wu, Fengwei Teng, Xiaojun Jia, Jiawei Xu, Jinyu Xiang, Yizhang Lin, Tianming Liu, Tongliang Liu, Yu Su, Huan Sun, Glen Berseth, Jianyun Nie, Ian T. Foster, Logan T. Ward, Qingyun Wu, Yu Gu, Mingchen Zhuge, Xiangru Tang, Haohan Wang, Jiaxuan You, Chi Wang, Jian Pei, Qiang Yang, Xiaoliang Qi, Chenglin Wu
2025	J	`jnl`	AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents. CoRR Hanjun Luo, Shenyu Dai, Chiming Ni, Xinfeng Li, Guibin Zhang, Kun Wang, Tongliang Liu, Hanan Salam
2025	J	`jnl`	Alignclip: navigating the misalignments for robust vision-language generalization. Mach. Learn. Zhongyi Han, Gongxu Luo, Hao Sun, Yaqian Li, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu
2025	J	`jnl`	Aligning Foundation Model Priors and Diffusion-Based Hand Interactions for Occlusion-Resistant Two-Hand Reconstruction. CoRR Gaoge Han, Yongkang Cheng, Zhe Chen, Shaoli Huang, Tongliang Liu
2025	J	`jnl`	AlphaApollo: Orchestrating Foundation Models and Professional Tools into a Self-Evolving System for Deep Agentic Reasoning. CoRR Zhanke Zhou, Chentao Cao, Xiao Feng, Xuan Li, Zongze Li, Xiangyu Lu, Jiangchao Yao, Weikai Huang, Linrui Xu, Tian Cheng, Guanyu Jiang, Yiming Zheng, Brando Miranda, Tongliang Liu, Sanmi Koyejo, Masashi Sugiyama, Bo Han
2025	J	`jnl`	Beyond Optimal Transport: Model-Aligned Coupling for Flow Matching. CoRR Yexiong Lin, Yu Yao, Tongliang Liu
2025	J	`jnl`	Can Large Language Models Help Experimental Design for Causal Discovery? CoRR Junyi Li, Yongqiang Chen, Chenxi Liu, Qianyi Cai, Tongliang Liu, Bo Han, Kun Zhang, Hui Xiong
2025	A*	`conf`	Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models. ICLR Jiyang Zheng, Jialiang Shen, Yu Yao, Min Wang, Yang Yang, Dadong Wang, Tongliang Liu
2025	J	`jnl`	Cognitive Mirrors: Exploring the Diverse Functional Roles of Attention Heads in LLM Reasoning. CoRR Xueqi Ma, Jun Wang, Yanbei Jiang, Sarah Monazam Erfani, Tongliang Liu, James Bailey
2025	A*	`conf`	DEEM: Diffusion models serve as the eyes of large language models for image perception. ICLR Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Hamid Rokny, Xiaobo Xia, Tongliang Liu, Binyuan Hui, Min Yang
2025	J	`jnl`	DINO-Detect: A Simple yet Effective Framework for Blur-Robust AI-Generated Image Detection. CoRR Jialiang Shen, Jiyang Zheng, Yunqi Xue, Huajie Chen, Yu Yao, Hui Kang, Ruiqi Liu, Helin Gong, Yang Yang, Dadong Wang, Tongliang Liu
2025	J	`jnl`	Defending Against Adversarial Examples Via Modeling Adversarial Noise. Int. J. Comput. Vis. Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu, Xinbo Gao
2025	J	`jnl`	Direct Advantage Regression: Aligning LLMs with Online AI Reward. CoRR Li He, He Zhao, Stephen Wan, Dadong Wang, Lina Yao, Tongliang Liu
2025	J	`jnl`	Does Representation Intervention Really Identify Desired Concepts and Elicit Alignment? CoRR Hongzheng Yang, Yongqiang Chen, Zeyu Qin, Tongliang Liu, Chaowei Xiao, Kun Zhang, Bo Han
2025	J	`jnl`	Early Stopping Against Label Noise Without Validation Data. CoRR Suqin Yuan, Lei Feng, Tongliang Liu
2025	A*	`conf`	Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations. ICLR Xiu-Chuan Li, Tongliang Liu
2025	J	`jnl`	Enhancing Sample Selection by Cutting Mislabeled Easy Examples. CoRR Suqin Yuan, Lei Feng, Bo Han, Tongliang Liu
2025	J	`jnl`	Estimating Per-Class Statistics for Label Noise Learning. IEEE Trans. Pattern Anal. Mach. Intell. Wenshui Luo, Shuo Chen, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama, Dacheng Tao, Chen Gong
2025	J	`jnl`	EvAnimate: Event-conditioned Image-to-Video Generation for Human Animation. CoRR Qiang Qu, Ming Li, Xiaoming Chen, Tongliang Liu
2025	A*	`conf`	Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning. ICML Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han
2025	J	`jnl`	Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning. CoRR Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han
2025	J	`jnl`	FORCE: Transferable Visual Jailbreaking Attacks via Feature Over-Reliance CorrEction. CoRR Runqi Lin, Alasdair Paren, Suqin Yuan, Muyang Li, Philip Torr, Adel Bibi, Tongliang Liu
2025	J	`jnl`	Flow: A Modular Approach to Automated Agentic Workflow Generation. CoRR Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu
2025	A*	`conf`	Flow: Modularized Agentic Workflow Automation. ICLR Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu
2025	J	`jnl`	Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning. CoRR Ali Taheri Ghahrizjani, Alireza Taban, Shanshan Ye, Abdolreza Mirzaei, Tongliang Liu, Bo Han
2025	J	`jnl`	Frequency-Based Comprehensive Prompt Learning for Vision-Language Models. IEEE Trans. Pattern Anal. Mach. Intell. Liangchen Liu, Nannan Wang, Chen Chen, Decheng Liu, Xi Yang, Xinbo Gao, Tongliang Liu
2025	J	`jnl`	From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium. CoRR Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han
2025	A*	`conf`	From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium. ICML Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han
2025	J	`jnl`	From Static to Dynamic: Adaptive Monte Carlo Search for Mathematical Process Supervision. CoRR Jie Ma, Shihao Qi, Rui Xing, Ziang Yin, Bifan Wei, Jun Liu, Tongliang Liu
2025	J	`jnl`	Generalizable Prompt Learning via Gradient Constrained Sharpness-Aware Minimization. IEEE Trans. Multim. Liangchen Liu, Nannan Wang, Dawei Zhou, Decheng Liu, Xi Yang, Xinbo Gao, Tongliang Liu
2025	J	`jnl`	Generative Model Inversion Through the Lens of the Manifold Hypothesis. CoRR Xiong Peng, Bo Han, Fengfei Yu, Tongliang Liu, Feng Liu, Mingyuan Zhou
2025	J	`jnl`	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization. IEEE Trans. Multim. Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang
2025	J	`jnl`	Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction. CoRR Xiaobo Xia, Xiaofeng Liu, Jiale Liu, Kuai Fang, Lu Lu, Samet Oymak, William S. Currie, Tongliang Liu
2025	J	`jnl`	Improving Adversarial Training From the Perspective of Class-Flipping Distribution. IEEE Trans. Pattern Anal. Mach. Intell. Dawei Zhou, Nannan Wang, Tongliang Liu, Xinbo Gao
2025	J	`jnl`	Improving the Instance-Dependent Transition Matrix Estimation by Exploiting Self-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. Yexiong Lin, Yu Yao, Zhaoqing Wang, Xu Shen, Jun Yu, Bo Han, Tongliang Liu
2025	A*	`conf`	Instance-dependent Early Stopping. ICLR Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu
2025	J	`jnl`	Instance-dependent Early Stopping. CoRR Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu
2025	J	`jnl`	Intern-GS: Vision Model Guided Sparse-View 3D Gaussian Splatting. CoRR Xiangyu Sun, Runnan Chen, Mingming Gong, Dong Xu, Tongliang Liu
2025	J	`jnl`	Investigating The Functional Roles of Attention Heads in Vision Language Models: Evidence for Reasoning Modules. CoRR Yanbei Jiang, Xueqi Ma, Shu Liu, Sarah Monazam Erfani, Tongliang Liu, James Bailey, Jey Han Lau, Krista A. Ehinger
2025	A*	`conf`	Jailbreaking the Non-Transferable Barrier via Test-Time Data Disguising. CVPR Yongli Xiang, Ziming Hong, Lina Yao, Dadong Wang, Tongliang Liu
2025	J	`jnl`	Jailbreaking the Non-Transferable Barrier via Test-Time Data Disguising. CoRR Yongli Xiang, Ziming Hong, Lina Yao, Dadong Wang, Tongliang Liu
2025	J	`jnl`	La La LiDAR: Large-Scale Layout Generation from LiDAR Data. CoRR Youquan Liu, Lingdong Kong, Weidong Yang, Xin Li, Ao Liang, Runnan Chen, Ben Fei, Tongliang Liu
2025	A*	`conf`	LaVin-DiT: Large Vision Diffusion Transformer. CVPR Zhaoqing Wang, Xiaobo Xia, Runnan Chen, Dongdong Yu, Changhu Wang, Mingming Gong, Tongliang Liu
2025	A*	`conf`	Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning. IJCAI Zhiqiang Kou, Si Qin, Hailin Wang, Jing Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng
2025	J	`jnl`	Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation. CoRR Zhiqiang Kou, Si Qin, Hailin Wang, Ming-Kun Xie, Shuo Chen, Yuheng Jia, Tongliang Liu, Masashi Sugiyama, Xin Geng
2025	J	`jnl`	Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering. CoRR Tianjun Yao, Haoxuan Li, Zhiqiang Shen, Pan Li, Tongliang Liu, Kun Zhang
2025	J	`jnl`	Learning General and Specific Embedding with Transformer for Few-Shot Object Detection. Int. J. Comput. Vis. Xu Zhang, Zhe Chen, Jing Zhang, Tongliang Liu, Dacheng Tao
2025	A*	`conf`	Learning Graph Invariance by Harnessing Spuriosity. ICLR Tianjun Yao, Yongqiang Chen, Kai Hu, Tongliang Liu, Kun Zhang, Zhiqiang Shen
2025	J	`jnl`	MF-VITON: High-Fidelity Mask-Free Virtual Try-On with Minimal Input. CoRR Zhenchen Wan, Yanwu Xu, Dongting Hu, Weilun Cheng, Tianxi Chen, Zhaoqing Wang, Feng Liu, Tongliang Liu, Mingming Gong
2025	—	`conf`	MFT-VITON: High-Fidelity Virtual Try-On with Minimal Input via a Mask-Free Transformer-Diffusion Model. ICCVW Zhenchen Wan, Yanwu Xu, Dongting Hu, Weilun Cheng, Tianxi Chen, Zhaoqing Wang, Feng Liu, Tongliang Liu, Mingming Gong
2025	J	`jnl`	MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation. CoRR Jiaxin Huang, Runnan Chen, Ziwen Li, Zhengqing Gao, Xiao He, Yandong Guo, Mingming Gong, Tongliang Liu
2025	J	`jnl`	MedDCR: Learning to Design Agentic Workflows for Medical Coding. CoRR Jiyang Zheng, Islam Nassar, Thanh Tien Vu, Xu Zhong, Yang Lin, Tongliang Liu, Long Duong, Yuan-Fang Li
2025	J	`jnl`	NVS-SQA: Exploring Self-Supervised Quality Representation Learning for Neurally Synthesized Scenes without References. CoRR Qiang Qu, Yiran Shen, Xiaoming Chen, Yuk Ying Chung, Tom Weidong Cai, Tongliang Liu
2025	A*	`conf`	Noisy Test-Time Adaptation in Vision-Language Models. ICLR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	J	`jnl`	Noisy Test-Time Adaptation in Vision-Language Models. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	J	`jnl`	OVGaussian: Generalizable 3D Gaussian Segmentation with Open Vocabularies. CoRR Runnan Chen, Xiangyu Sun, Zhaoqing Wang, Youquan Liu, Jiepeng Wang, Lingdong Kong, Jiankang Deng, Mingming Gong, Liang Pan, Wenping Wang, Tongliang Liu
2025	J	`jnl`	On the Thinking-Language Modeling Gap in Large Language Models. CoRR Chenxi Liu, Yongqiang Chen, Tongliang Liu, James Cheng, Bo Han, Kun Zhang
2025	—	`conf`	OpenInsGaussian: Open-Vocabulary Instance Gaussian Segmentation with Context-Aware Cross-View Fusion. ICCVW Tianyu Huang, Runnan Chen, Dongting Hu, Fengming Huang, Mingming Gong, Tongliang Liu
2025	J	`jnl`	OpenInsGaussian: Open-vocabulary Instance Gaussian Segmentation with Context-aware Cross-view Fusion. CoRR Tianyu Huang, Runnan Chen, Dongting Hu, Fengming Huang, Mingming Gong, Tongliang Liu
2025	J	`jnl`	PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAM. CoRR Runnan Chen, Zhaoqing Wang, Jiepeng Wang, Yuexin Ma, Mingming Gong, Wenping Wang, Tongliang Liu
2025	J	`jnl`	Plan before Solving: Problem-Aware Strategy Routing for Mathematical Reasoning with LLMs. CoRR Shihao Qi, Jie Ma, Ziang Yin, Lingling Zhang, Jian Zhang, Jun Liu, Feng Tian, Tongliang Liu
2025	J	`jnl`	PosA-VLA: Enhancing Action Generation via Pose-Conditioned Anchor Attention. CoRR Ziwen Li, Xin Wang, Hanlue Zhang, Runnan Chen, Runqi Lin, Xiao He, Han Huang, Yandong Guo, Fakhri Karray, Tongliang Liu, Mingming Gong
2025	J	`jnl`	Power Characterization of Noisy Quantum Kernels. IEEE Trans. Neural Networks Learn. Syst. Yabo Wang, Bo Qi, Xin Wang, Tongliang Liu, Daoyi Dong
2025	J	`jnl`	Prompt-Based Multi-Interest Learning Method for Sequential Recommendation. IEEE Trans. Pattern Anal. Mach. Intell. Xue Dong, Xuemeng Song, Tongliang Liu, Weili Guan
2025	J	`jnl`	ProtoGS: Efficient and High-Quality Rendering with 3D Gaussian Prototypes. CoRR Zhengqing Gao, Dongting Hu, Jia-Wang Bian, Huan Fu, Yan Li, Tongliang Liu, Mingming Gong, Kun Zhang
2025	A*	`conf`	Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection. AAAI Zhipeng Zou, Sheng Wan, Guangyu Li, Bo Han, Tongliang Liu, Lin Zhao, Chen Gong
2025	J	`jnl`	Pruning Spurious Subgraphs for Graph Out-of-Distribtuion Generalization. CoRR Tianjun Yao, Haoxuan Li, Yongqiang Chen, Tongliang Liu, Le Song, Eric P. Xing, Zhiqiang Shen
2025	J	`jnl`	RDSplat: Robust Watermarking Against Diffusion Editing for 3D Gaussian Splatting. CoRR Longjie Zhao, Ziming Hong, Zhenyang Ren, Runnan Chen, Mingming Gong, Tongliang Liu
2025	A*	`conf`	Ranked from Within: Ranking Large Multimodal Models Without Labels. ICML Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu
2025	A*	`conf`	Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates. ICLR Xiu-Chuan Li, Jun Wang, Tongliang Liu
2025	J	`jnl`	Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers. CoRR Xin-Qiang Cai, Wei Wang, Feng Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama
2025	J	`jnl`	Revealing Multimodal Causality with Large Language Models. CoRR Jin Li, Shoujin Wang, Qi Zhang, Feng Liu, Tongliang Liu, Longbing Cao, Shui Yu, Fang Chen
2025	J	`jnl`	SURPRISE3D: A Dataset for Spatial Understanding and Reasoning in Complex 3D Scenes. CoRR Jiaxin Huang, Ziwen Li, Hanlve Zhang, Runnan Chen, Xiao He, Yandong Guo, Wenping Wang, Tongliang Liu, Mingming Gong
2025	J	`jnl`	Safety at Scale: A Comprehensive Survey of Large Model Safety. CoRR Xingjun Ma, Yifeng Gao, Yixu Wang, Ruofan Wang, Xin Wang, Ye Sun, Yifan Ding, Hengyuan Xu, Yunhao Chen, Yunhan Zhao, Hanxun Huang, Yige Li, Jiaming Zhang, Xiang Zheng, Yang Bai, Zuxuan Wu, Xipeng Qiu, Jingfeng Zhang, Yiming Li, Jun Sun, Cong Wang, Jindong Gu, Baoyuan Wu, Siheng Chen, Tianwei Zhang, Yang Liu, Mingming Gong, Tongliang Liu, Shirui Pan, Cihang Xie, Tianyu Pang, Yinpeng Dong, Ruoxi Jia, Yang Zhang, Shiqing Ma, Xiangyu Zhang, Neil Gong, Chaowei Xiao, Sarah M. Erfani, Bo Li, Masashi Sugiyama, Dacheng Tao, James Bailey, Yu-Gang Jiang
2025	J	`jnl`	Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety. Found. Trends Priv. Secur. Xingjun Ma, Yifeng Gao, Yixu Wang, Ruofan Wang, Xin Wang, Ye Sun, Yifan Ding, Hengyuan Xu, Yunhao Chen, Yunhao Zhao, Hanxun Huang, Yige Li, Yutao Wu, Jiaming Zhang, Xiang Zheng, Yang Bai, Yiming Li, Zuxuan Wu, Xipeng Qiu, Jingfeng Zhang, Xudong Han, Haonan Li, Jun Sun, Cong Wang, Jindong Gu, Baoyuan Wu, Siheng Chen, Tianwei Zhang, Yang Liu, Mingming Gong, Tongliang Liu, Shirui Pan, Cihang Xie, Tianyu Pang, Yinpeng Dong, Ruoxi Jia, Yang Zhang, Shiqing Ma, Xiangyu Zhang, Neil Gong, Chaowei Xiao, Sarah M. Erfani, Tim Baldwin, Bo Li, Masashi Sugiyama, Dacheng Tao, James Bailey, Yu-Gang Jiang
2025	J	`jnl`	State space models can express Trans. Mach. Learn. Res. Vinoth Nandakumar, Qiang Qu, Peng Mi, Tongliang Liu
2025	A*	`conf`	Surrogate Prompt Learning: Towards Efficient and Diverse Prompt Learning for Vision-Language Models. ICML Liangchen Liu, Nannan Wang, Xi Yang, Xinbo Gao, Tongliang Liu
2025	J	`jnl`	Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer. IEEE Trans. Pattern Anal. Mach. Intell. Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Tianshuo Xu, Xiaoshuai Sun, Tongliang Liu, Rongrong Ji, Dacheng Tao
2025	A*	`conf`	Toward Robust Non-Transferable Learning: A Survey and Benchmark. IJCAI Ziming Hong, Yongli Xiang, Tongliang Liu
2025	J	`jnl`	Toward Robust Non-Transferable Learning: A Survey and Benchmark. CoRR Ziming Hong, Yongli Xiang, Tongliang Liu
2025	A*	`conf`	Towards Effective Evaluations and Comparisons for LLM Unlearning Methods. ICLR Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama
2025	A*	`conf`	Towards Out-of-Modal Generalization without Instance-level Modal Correspondence. ICLR Zhuo Huang, Gang Niu, Bo Han, Masashi Sugiyama, Tongliang Liu
2025	J	`jnl`	Trustworthy Machine Learning: From Data to Models. Found. Trends Priv. Secur. Bo Han, Jiangchao Yao, Tongliang Liu, Bo Li, Sanmi Koyejo, Feng Liu
2025	A*	`conf`	Understanding and Enhancing the Transferability of Jailbreaking Attacks. ICLR Runqi Lin, Bo Han, Fengwang Li, Tongliang Liu
2025	J	`jnl`	Unknown-Aware Bilateral Dependency Optimization for Defending Against Model Inversion Attacks. IEEE Trans. Pattern Anal. Mach. Intell. Xiong Peng, Feng Liu, Nannan Wang, Long Lan, Tongliang Liu, Yiu-ming Cheung, Bo Han
2025	J	`jnl`	Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? CoRR Haoang Chi, He Li, Wenjing Yang, Feng Liu, Long Lan, Xiaoguang Ren, Tongliang Liu, Bo Han
2025	J	`jnl`	W-DOE: Wasserstein Distribution-Agnostic Outlier Exposure. IEEE Trans. Pattern Anal. Mach. Intell. Qizhou Wang, Bo Han, Yang Liu, Chen Gong, Tongliang Liu, Jiming Liu
2025	A*	`conf`	When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need. ICML Ziming Hong, Runnan Chen, Zengmao Wang, Bo Han, Bo Du, Tongliang Liu
2025	J	`jnl`	When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need. CoRR Ziming Hong, Runnan Chen, Zengmao Wang, Bo Han, Bo Du, Tongliang Liu
2025	J	`jnl`	Winning Prize Comes from Losing Tickets: Improve Invariant Learning by Exploring Variant Parameters for Out-of-Distribution Generalization. Int. J. Comput. Vis. Zhuo Huang, Muyang Li, Li Shen, Jun Yu, Chen Gong, Bo Han, Tongliang Liu
2024	J	`jnl`	A Time-Consistency Curriculum for Learning From Instance-Dependent Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. Songhua Wu, Tianyi Zhou, Yuxuan Du, Jun Yu, Bo Han, Tongliang Liu
2024	—	`ed.`	AI 2023: Advances in Artificial Intelligence - 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, Brisbane, QLD, Australia, November 28 - December 1, 2023, Proceedings, Part I AI (1) Tongliang Liu, Geoffrey I. Webb, Lin Yue, Dadong Wang
2024	—	`ed.`	AI 2023: Advances in Artificial Intelligence - 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, Brisbane, QLD, Australia, November 28 - December 1, 2023, Proceedings, Part II AI (2) Tongliang Liu, Geoffrey I. Webb, Lin Yue, Dadong Wang
2024	J	`jnl`	BadLabel: A Robust Perspective on Evaluating and Enhancing Label-Noise Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama
2024	J	`jnl`	Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels. CoRR Haodong Chen, Runnan Chen, Qiang Qu, Zhaoqing Wang, Tongliang Liu, Xiaoming Chen, Yuk Ying Chung
2024	J	`jnl`	Can We Treat Noisy Labels as Accurate? CoRR Yuxiang Zheng, Zhongyi Han, Yilong Yin, Xin Gao, Tongliang Liu
2024	A*	`conf`	Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions. ICLR Xiu-Chuan Li, Kun Zhang, Tongliang Liu
2024	J	`jnl`	Class-Wise Contrastive Prototype Learning for Semi-Supervised Classification Under Intersectional Class Mismatch. IEEE Trans. Multim. Mingyu Li, Tao Zhou, Bo Han, Tongliang Liu, Xinkai Liang, Jiajia Zhao, Chen Gong
2024	J	`jnl`	Conditional Consistency Regularization for Semi-Supervised Multi-Label Image Classification. IEEE Trans. Multim. Zhengning Wu, Tianyu He, Xiaobo Xia, Jun Yu, Xu Shen, Tongliang Liu
2024	J	`jnl`	Continual Learning From a Stream of APIs. IEEE Trans. Pattern Anal. Mach. Intell. Enneng Yang, Zhenyi Wang, Li Shen, Nan Yin, Tongliang Liu, Guibing Guo, Xingwei Wang, Dacheng Tao
2024	J	`jnl`	DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception. CoRR Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Xiaobo Xia, Tongliang Liu, Min Yang, Binyuan Hui
2024	A*	`conf`	Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization. NeurIPS Hongling Zheng, Li Shen, Yong Luo, Tongliang Liu, Jialie Shen, Dacheng Tao
2024	J	`jnl`	Detecting Discrepancies Between AI-Generated and Natural Images Using Uncertainty. CoRR Jun Nie, Yonggang Zhang, Tongliang Liu, Yiu-ming Cheung, Bo Han, Xinmei Tian
2024	A*	`conf`	Discovery of the Hidden World with Large Language Models. NeurIPS Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang
2024	J	`jnl`	Discovery of the Hidden World with Large Language Models. CoRR Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang
2024	A*	`conf`	E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning. AAAI Qiang Qu, Yiran Shen, Xiaoming Chen, Yuk Ying Chung, Tongliang Liu
2024	J	`jnl`	E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning. CoRR Qiang Qu, Yiran Shen, Xiaoming Chen, Yuk Ying Chung, Tongliang Liu
2024	A	`conf`	ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance. CIKM Ling-Hao Chen, Yuanshuo Zhang, Taohua Huang, Liangcai Su, Zeyi Lin, Xi Xiao, Xiaobo Xia, Tongliang Liu
2024	A*	`conf`	Early Stopping Against Label Noise Without Validation Data. ICLR Suqin Yuan, Lei Feng, Tongliang Liu
2024	J	`jnl`	Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization. CoRR Runqi Lin, Chaojian Yu, Tongliang Liu
2024	A*	`conf`	Enhanced Motion-Text Alignment for Image-to-Video Transfer Learning. CVPR Wei Zhang, Chaoqun Wan, Tongliang Liu, Xinmei Tian, Xu Shen, Jieping Ye
2024	A*	`conf`	Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation. ICLR Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu
2024	A*	`conf`	Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting. ICLR Rong Dai, Yonggang Zhang, Ang Li, Tongliang Liu, Xun Yang, Bo Han
2024	J	`jnl`	Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting. CoRR Rong Dai, Yonggang Zhang, Ang Li, Tongliang Liu, Xun Yang, Bo Han
2024	J	`jnl`	Enhancing User-Centric Privacy Protection: An Interactive Framework through Diffusion Models and Machine Unlearning. CoRR Huaxi Huang, Xin Yu, Qiyu Liao, Dadong Wang, Tongliang Liu
2024	A*	`conf`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. ICML Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	J	`jnl`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	J	`jnl`	Expansion of the editorial team. Neural Networks DeLiang Wang, Mauro Forti, Tongliang Liu, Taro Toyoizumi
2024	J	`jnl`	Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation. Trans. Mach. Learn. Res. Wankou Yang, Jiren Mai, Fei Zhang, Tongliang Liu, Bo Han
2024	A*	`conf`	Exploring Channel-Aware Typical Features for Out-of-Distribution Detection. AAAI Rundong He, Yue Yuan, Zhongyi Han, Fan Wang, Wan Su, Yilong Yin, Tongliang Liu, Yongshun Gong
2024	J	`jnl`	Extracting Clean and Balanced Subset for Noisy Long-tailed Classification. CoRR Zhuo Li, He Zhao, Zhen Li, Tongliang Liu, Dandan Guo, Xiang Wan
2024	A*	`conf`	FedImpro: Measuring and Improving Client Update in Federated Learning. ICLR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu
2024	J	`jnl`	FedImpro: Measuring and Improving Client Update in Federated Learning. CoRR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu
2024	A*	`conf`	Federated Causal Discovery from Heterogeneous Data. ICLR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	J	`jnl`	Federated Causal Discovery from Heterogeneous Data. CoRR Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024	A*	`conf`	Few-Shot Adversarial Prompt Learning on Vision-Language Models. NeurIPS Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu
2024	J	`jnl`	Few-Shot Adversarial Prompt Learning on Vision-Language Models. CoRR Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu
2024	J	`jnl`	Finding core labels for maximizing generalization of graph neural networks. Neural Networks Sichao Fu, Xueqi Ma, Yibing Zhan, Fanyu You, Qinmu Peng, Tongliang Liu, James Bailey, Danilo P. Mandic
2024	J	`jnl`	Going Deeper, Generalizing Better: An Information-Theoretic View for Deep Learning. IEEE Trans. Neural Networks Learn. Syst. Jingwei Zhang, Tongliang Liu, Dacheng Tao
2024	J	`jnl`	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization. CoRR Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang
2024	A*	`conf`	IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models. ICLR Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu
2024	J	`jnl`	Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations. J. Mach. Learn. Res. Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao
2024	A*	`conf`	Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training. ICML Jiacheng Zhang, Feng Liu, Dawei Zhou, Jingfeng Zhang, Tongliang Liu
2024	J	`jnl`	Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training. CoRR Jiacheng Zhang, Feng Liu, Dawei Zhou, Jingfeng Zhang, Tongliang Liu
2024	A*	`conf`	Improving Non-Transferable Representation Learning by Harnessing Content and Style. ICLR Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu
2024	A*	`conf`	In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment. NeurIPS Dongting Hu, Huan Fu, Jiaxian Guo, Liuhua Peng, Tingjin Chu, Feng Liu, Tongliang Liu, Mingming Gong
2024	J	`jnl`	Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning. CoRR Tianfu Wang, Li Shen, Qilin Fan, Tong Xu, Tongliang Liu, Hui Xiong
2024	J	`jnl`	Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning. IEEE Trans. Serv. Comput. Tianfu Wang, Li Shen, Qilin Fan, Tong Xu, Tongliang Liu, Hui Xiong
2024	J	`jnl`	LaVin-DiT: Large Vision Diffusion Transformer. CoRR Zhaoqing Wang, Xiaobo Xia, Runnan Chen, Dongdong Yu, Changhu Wang, Mingming Gong, Tongliang Liu
2024	A*	`conf`	Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency. ICML Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu
2024	J	`jnl`	Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency. CoRR Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu
2024	J	`jnl`	Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels. CoRR Yuxin Tian, Mouxing Yang, Yuhao Zhou, Jian Wang, Qing Ye, Tongliang Liu, Gang Niu, Jiancheng Lv
2024	A*	`conf`	Learning the Latent Causal Structure for Modeling Label Noise. NeurIPS Yexiong Lin, Yu Yao, Tongliang Liu
2024	A*	`conf`	MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence. ICML Hongduan Tian, Feng Liu, Tongliang Liu, Bo Du, Yiu-ming Cheung, Bo Han
2024	J	`jnl`	MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence. CoRR Hongduan Tian, Feng Liu, Tongliang Liu, Bo Du, Yiu-ming Cheung, Bo Han
2024	A*	`conf`	Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning. ICML Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu
2024	A*	`conf`	Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. NeurIPS Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han
2024	J	`jnl`	Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. CoRR Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han
2024	J	`jnl`	Mitigating Label Noise on Graph via Topological Sample Selection. CoRR Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu
2024	A*	`conf`	Mitigating Label Noise on Graphs via Topological Sample Selection. ICML Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu
2024	J	`jnl`	Model Inversion Attacks: A Survey of Approaches and Countermeasures. CoRR Zhanke Zhou, Jianing Zhu, Fengfei Yu, Xuan Li, Xiong Peng, Tongliang Liu, Bo Han
2024	—	`conf`	Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. AI (2) Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu
2024	A*	`conf`	Negative Label Guided OOD Detection with Pretrained Vision-Language Models. ICLR Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2024	J	`jnl`	Negative Label Guided OOD Detection with Pretrained Vision-Language Models. CoRR Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2024	A*	`conf`	Neural Auto-designer for Enhanced Quantum Kernels. ICLR Cong Lei, Yuxuan Du, Peng Mi, Jun Yu, Tongliang Liu
2024	J	`jnl`	Neural auto-designer for enhanced quantum kernels. CoRR Cong Lei, Yuxuan Du, Peng Mi, Jun Yu, Tongliang Liu
2024	A*	`conf`	NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation. ICLR Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han
2024	J	`jnl`	NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation. CoRR Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han
2024	A*	`conf`	NoiseGPT: Label Noise Detection and Rectification through Probability Curvature. NeurIPS Haoyu Wang, Zhuo Huang, Zhiwei Lin, Tongliang Liu
2024	J	`jnl`	On Intriguing Layer-Wise Properties of Robust Overfitting in Adversarial Training. Trans. Mach. Learn. Res. Duke Nguyen, Chaojian Yu, Vinoth Nandakumar, Young Choon Lee, Tongliang Liu
2024	A*	`conf`	On the Over-Memorization During Natural, Robust and Catastrophic Overfitting. ICLR Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu
2024	—	`conf`	One-Shot Learning as Instruction Data Prospector for Large Language Models. ACL (1) Yunshui Li, Binyuan Hui, Xiaobo Xia, Jiaxi Yang, Min Yang, Lei Zhang, Shuzheng Si, Ling-Hao Chen, Junhao Liu, Tongliang Liu, Fei Huang, Yongbin Li
2024	J	`jnl`	Open-Vocabulary Segmentation with Unpaired Mask-Text Supervision. CoRR Zhaoqing Wang, Xiaobo Xia, Ziye Chen, Xiao He, Yandong Guo, Mingming Gong, Tongliang Liu
2024	A*	`conf`	Optimal Kernel Choice for Score Function-based Causal Discovery. ICML Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong
2024	J	`jnl`	Optimal Kernel Choice for Score Function-based Causal Discovery. CoRR Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong
2024	A*	`conf`	Out-of-Distribution Detection with Negative Prompts. ICLR Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian
2024	J	`jnl`	Prompt-based Multi-interest Learning Method for Sequential Recommendation. CoRR Xue Dong, Xuemeng Song, Tongliang Liu, Weili Guan
2024	J	`jnl`	ProtoSimi: label correction for fine-grained visual categorization. Mach. Learn. Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu
2024	A*	`conf`	Pseudo-Private Data Guided Model Inversion Attacks. NeurIPS Xiong Peng, Bo Han, Feng Liu, Tongliang Liu, Mingyuan Zhou
2024	J	`jnl`	QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge. CoRR Hongwei Bran Li, Fernando Navarro, Ivan Ezhov, Amirhossein Bayat, Dhritiman Das, Florian Kofler, Suprosanna Shit, Diana Waldmannstetter, Johannes C. Paetzold, Xiaobin Hu, Benedikt Wiestler, Lucas Zimmer, Tamaz Amiranashvili, Chinmay Prabhakar, Christoph Berger, Jonas Weidner, Michelle Alonso-Basanta, Arif Rashid, Ujjwal Baid, Wesam Adel, Deniz Alis, Bhakti Baheti, Yingbin Bai, Ishaan Bhat, Sabri Can Cetindag, Wenting Chen, Li Cheng, Prasad Dutande, Lara Dular, Mustafa A. Elattar, Ming Feng, Shengbo Gao, Henkjan Huisman, Weifeng Hu, Shubham Innani, Wei Jiat, Davood Karimi, Hugo J. Kuijf, Jin Tae Kwak, Hoang Long Le, Xiang Lia, Huiyan Lin, Tongliang Liu, Jun Ma, Kai Ma, Ting Ma, Ilkay Öksüz, Robbie Holland, Arlindo L. Oliveira, Jimut Bahan Pal, Xuan Pei, Maoying Qiao, Anindo Saha, Raghavendra Selvan, Linlin Shen, João Lourenço Silva, Ziga Spiclin, Sanjay N. Talbar, Dadong Wang, Wei Wang, Xiong Wang, Yin Wang, Ruiling Xia, Kele Xu, Yanwu Yan, Mert Yergin, Shuang Yu, Lingxi Zeng, YingLin Zhang, Jiachen Zhao, Yefeng Zheng, Martin Zukovec, Richard K. G. Do, Anton S. Becker, Amber L. Simpson, Ender Konukoglu, András Jakab, Spyridon Bakas, Leo Joskowicz, Bjoern H. Menze
2024	J	`jnl`	Quantization Aware Attack: Enhancing Transferable Adversarial Attacks by Model Quantization. IEEE Trans. Inf. Forensics Secur. Yulong Yang, Chenhao Lin, Qian Li, Zhengyu Zhao, Haoran Fan, Dawei Zhou, Nannan Wang, Tongliang Liu, Chao Shen
2024	J	`jnl`	Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels. CoRR Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu
2024	A*	`conf`	Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints. ICML Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Hongxin Wei, Tongliang Liu
2024	J	`jnl`	Regularly Truncated M-Estimators for Learning With Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. Xiaobo Xia, Pengqian Lu, Chen Gong, Bo Han, Jun Yu, Jun Yu, Tongliang Liu
2024	J	`jnl`	Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection. CoRR Yewen Li, Chaojie Wang, Xiaobo Xia, Xu He, Ruyi An, Dong Li, Tongliang Liu, Bo An, Xinrun Wang
2024	A*	`conf`	Robust Training of Federated Models with Extremely Label Deficiency. ICLR Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han
2024	J	`jnl`	Robust Training of Federated Models with Extremely Label Deficiency. CoRR Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han
2024	J	`jnl`	TED-VITON: Transformer-Empowered Diffusion Models for Virtual Try-On. CoRR Zhenchen Wan, Yanwu Xu, Zhaoqing Wang, Feng Liu, Tongliang Liu, Mingming Gong
2024	J	`jnl`	Tackling Noisy Labels With Network Parameter Additive Decomposition. IEEE Trans. Pattern Anal. Mach. Intell. Jingyi Wang, Xiaobo Xia, Long Lan, Xinghao Wu, Jun Yu, Wenjing Yang, Bo Han, Tongliang Liu
2024	J	`jnl`	Tackling Noisy Labels with Network Parameter Additive Decomposition. CoRR Jingyi Wang, Xiaobo Xia, Long Lan, Xinghao Wu, Jun Yu, Wenjing Yang, Bo Han, Tongliang Liu
2024	A*	`conf`	Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning. ICML Yusong Hu, De Cheng, Dingwen Zhang, Nannan Wang, Tongliang Liu, Xinbo Gao
2024	A*	`conf`	Towards Realistic Model Selection for Semi-supervised Learning. ICML Muyang Li, Xiaobo Xia, Runze Wu, Fengming Huang, Jun Yu, Bo Han, Tongliang Liu
2024	J	`jnl`	Towards Specific Domain Prompt Learning via Improved Text Label Optimization. IEEE Trans. Multim. Liangchen Liu, Nannan Wang, Decheng Liu, Xi Yang, Xinbo Gao, Tongliang Liu
2024	—	`conf`	Training A Secure Model Against Data-Free Model Extraction. ECCV (79) Zhenyi Wang, Li Shen, Junfeng Guo, Tiehang Duan, Siyu Luan, Tongliang Liu, Mingchen Gao
2024	J	`jnl`	Training-Free Robust Interactive Video Object Segmentation. CoRR Xiaoli Wei, Zhaoqing Wang, Yandong Guo, Chunxia Zhang, Tongliang Liu, Mingming Gong
2024	J	`jnl`	Transferring Annotator- and Instance-Dependent Transition Matrix for Learning From Crowds. IEEE Trans. Pattern Anal. Mach. Intell. Shikun Li, Xiaobo Xia, Jiankang Deng, Shiming Ge, Tongliang Liu
2024	J	`jnl`	Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning. CoRR Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama
2024	A*	`conf`	Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning. ICML Yuhao Wu, Jiangchao Yao, Bo Han, Lina Yao, Tongliang Liu
2024	J	`jnl`	Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning. CoRR Yuhao Wu, Jiangchao Yao, Bo Han, Lina Yao, Tongliang Liu
2024	A*	`conf`	Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? NeurIPS Haoang Chi, He Li, Wenjing Yang, Feng Liu, Long Lan, Xiaoguang Ren, Tongliang Liu, Bo Han
2024	J	`jnl`	Urban4D: Semantic-Guided 4D Gaussian Splatting for Urban Scene Reconstruction. CoRR Ziwen Li, Jiaxin Huang, Runnan Chen, Yunlong Che, Yandong Guo, Tongliang Liu, Fakhri Karray, Mingming Gong
2024	A*	`conf`	What If the Input is Expanded in OOD Detection? NeurIPS Boxuan Zhang, Jianing Zhu, Zengmao Wang, Tongliang Liu, Bo Du, Bo Han
2024	J	`jnl`	What If the Input is Expanded in OOD Detection? CoRR Boxuan Zhang, Jianing Zhu, Zengmao Wang, Tongliang Liu, Bo Du, Bo Han
2024	A*	`conf`	Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning. CVPR Ziming Hong, Li Shen, Tongliang Liu
2023	A*	`conf`	A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond. ICLR Yong Lin, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han
2023	J	`jnl`	A Parametrical Model for Instance-Dependent Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. Shuo Yang, Songhua Wu, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2023	A*	`conf`	A Universal Unbiased Method for Classification from Aggregate Observations. ICML Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen
2023	J	`jnl`	A Universal Unbiased Method for Classification from Aggregate Observations. CoRR Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen
2023	A*	`conf`	ALIP: Adaptive Language-Image Pre-training with Synthetic Caption. ICCV Kaicheng Yang, Jiankang Deng, Xiang An, Jiawei Li, Ziyong Feng, Jia Guo, Jing Yang, Tongliang Liu
2023	J	`jnl`	ALIP: Adaptive Language-Image Pre-training with Synthetic Caption. CoRR Kaicheng Yang, Jiankang Deng, Xiang An, Jiawei Li, Ziyong Feng, Jia Guo, Jing Yang, Tongliang Liu
2023	J	`jnl`	Advancing Counterfactual Inference through Quantile Regression. CoRR Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang
2023	A*	`conf`	An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. NeurIPS Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo
2023	J	`jnl`	An Optimal Transport Analysis on Generalization in Deep Learning. IEEE Trans. Neural Networks Learn. Syst. Jingwei Zhang, Tongliang Liu, Dacheng Tao
2023	A*	`conf`	Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning. CVPR Zixuan Hu, Li Shen, Zhenyi Wang, Tongliang Liu, Chun Yuan, Dacheng Tao
2023	J	`jnl`	Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning. CoRR Zixuan Hu, Li Shen, Zhenyi Wang, Tongliang Liu, Chun Yuan, Dacheng Tao
2023	J	`jnl`	BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning. CoRR Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama
2023	A*	`conf`	BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency. CVPR Shuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu
2023	J	`jnl`	BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency. CoRR Shuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu
2023	A*	`conf`	CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation. NeurIPS Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu
2023	J	`jnl`	Channel-Wise Contrastive Learning for Learning with Noisy Labels. CoRR Hui Kang, Sheng Liu, Huaxi Huang, Tongliang Liu
2023	A*	`conf`	Combating Exacerbated Heterogeneity for Robust Models in Federated Learning. ICLR Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han
2023	J	`jnl`	Combating Exacerbated Heterogeneity for Robust Models in Federated Learning. CoRR Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han
2023	A*	`conf`	Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples. ICCV Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu
2023	A*	`conf`	Contextual Convolutional Networks. ICLR Shuxian Liang, Xu Shen, Tongliang Liu, Xian-Sheng Hua
2023	J	`jnl`	Continual Learning From a Stream of APIs. CoRR Enneng Yang, Zhenyi Wang, Li Shen, Nan Yin, Tongliang Liu, Guibing Guo, Xingwei Wang, Dacheng Tao
2023	J	`jnl`	Coreset Selection with Prioritized Multiple Objectives. CoRR Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Tongliang Liu
2023	J	`jnl`	DeepInception: Hypnotize Large Language Model to Be Jailbreaker. CoRR Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han
2023	J	`jnl`	DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Text Spotting. CoRR Maoyuan Ye, Jing Zhang, Shanshan Zhao, Juhua Liu, Tongliang Liu, Bo Du, Dacheng Tao
2023	A*	`conf`	DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting. CVPR Maoyuan Ye, Jing Zhang, Shanshan Zhao, Juhua Liu, Tongliang Liu, Bo Du, Dacheng Tao
2023	A*	`conf`	Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training. NeurIPS Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David S. Doermann, Mingchen Gao
2023	A*	`conf`	Detecting Out-of-distribution Data through In-distribution Class Prior. ICML Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2023	A*	`conf`	Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation. NeurIPS Jianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han
2023	J	`jnl`	Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation. CoRR Jianing Zhu, Geng Yu, Jiangchao Yao, Tongliang Liu, Gang Niu, Masashi Sugiyama, Bo Han
2023	A*	`conf`	Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation. ICML Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han
2023	J	`jnl`	Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation. CoRR Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han
2023	J	`jnl`	Dynamics-Aware Loss for Learning with Label Noise. CoRR Xiu-Chuan Li, Xiaobo Xia, Fei Zhu, Tongliang Liu, Xu-Yao Zhang, Cheng-Lin Liu
2023	J	`jnl`	Dynamics-aware loss for learning with label noise. Pattern Recognit. Xiu-Chuan Li, Xiaobo Xia, Fei Zhu, Tongliang Liu, Xu-Yao Zhang, Cheng-Lin Liu
2023	J	`jnl`	ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance. CoRR Linghao Chen, Yuanshuo Zhang, Taohua Huang, Liangcai Su, Zeyi Lin, Xi Xiao, Xiaobo Xia, Tongliang Liu
2023	A*	`conf`	Eliminating Adversarial Noise via Information Discard and Robust Representation Restoration. ICML Dawei Zhou, Yukun Chen, Nannan Wang, Decheng Liu, Xinbo Gao, Tongliang Liu
2023	A*	`conf`	Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization. NeurIPS Runqi Lin, Chaojian Yu, Tongliang Liu
2023	A*	`conf`	Evolving Semantic Prototype Improves Generative Zero-Shot Learning. ICML Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang
2023	J	`jnl`	Evolving Semantic Prototype Improves Generative Zero-Shot Learning. CoRR Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang
2023	J	`jnl`	Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation. CoRR Jiren Mai, Fei Zhang, Junjie Ye, Marcus Kalander, Xian Zhang, Wankou Yang, Tongliang Liu, Bo Han
2023	A*	`conf`	Exploring Model Dynamics for Accumulative Poisoning Discovery. ICML Jianing Zhu, Xiawei Guo, Jiangchao Yao, Chao Du, Li He, Shuo Yuan, Tongliang Liu, Liang Wang, Bo Han
2023	J	`jnl`	Exploring Model Dynamics for Accumulative Poisoning Discovery. CoRR Jianing Zhu, Xiawei Guo, Jiangchao Yao, Chao Du, Li He, Shuo Yuan, Tongliang Liu, Liang Wang, Bo Han
2023	J	`jnl`	Extended $T$T: Learning With Mixed Closed-Set and Open-Set Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. Xiaobo Xia, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao, Tongliang Liu
2023	J	`jnl`	Fairness Improves Learning from Noisily Labeled Long-Tailed Data. CoRR Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu
2023	J	`jnl`	FedDAG: Federated DAG Structure Learning. Trans. Mach. Learn. Res. Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard D. Bondell
2023	A*	`conf`	FedFed: Feature Distillation against Data Heterogeneity in Federated Learning. NeurIPS Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han
2023	J	`jnl`	FedFed: Feature Distillation against Data Heterogeneity in Federated Learning. CoRR Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, Bo Han
2023	A*	`conf`	FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning. NeurIPS Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu
2023	J	`jnl`	FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning. CoRR Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu
2023	J	`jnl`	Gradient constrained sharpness-aware prompt learning for vision-language models. CoRR Liangchen Liu, Nannan Wang, Dawei Zhou, Xinbo Gao, Decheng Liu, Xi Yang, Tongliang Liu
2023	A*	`conf`	Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities. IJCAI Chuang Liu, Yibing Zhan, Jia Wu, Chang Li, Bo Du, Wenbin Hu, Tongliang Liu, Dacheng Tao
2023	J	`jnl`	Handling Open-Set Noise and Novel Target Recognition in Domain Adaptive Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. Xiaoqing Guo, Jie Liu, Tongliang Liu, Yixuan Yuan
2023	A*	`conf`	Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. ICLR Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
2023	A*	`conf`	Holistic Label Correction for Noisy Multi-Label Classification. ICCV Xiaobo Xia, Jiankang Deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu
2023	J	`jnl`	How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation. CoRR Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Tailin Wu, Yilong Yin, Salman H. Khan, Lina Yao, Tongliang Liu, Kun Zhang
2023	A*	`conf`	HumanMAC: Masked Motion Completion for Human Motion Prediction. ICCV Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu
2023	J	`jnl`	HumanMAC: Masked Motion Completion for Human Motion Prediction. CoRR Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu
2023	J	`jnl`	IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models. CoRR Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu
2023	A*	`conf`	InstanT: Semi-supervised Learning with Instance-dependent Thresholds. NeurIPS Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, Tongliang Liu
2023	J	`jnl`	InstanT: Semi-supervised Learning with Instance-dependent Thresholds. CoRR Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, Tongliang Liu
2023	J	`jnl`	KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation. Trans. Mach. Learn. Res. Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, Kwok-Wai Cheung, Bo Han
2023	A*	`conf`	Late Stopping: Avoiding Confidently Learning from Mislabeled Examples. ICCV Suqin Yuan, Lei Feng, Tongliang Liu
2023	J	`jnl`	Late Stopping: Avoiding Confidently Learning from Mislabeled Examples. CoRR Suqin Yuan, Lei Feng, Tongliang Liu
2023	J	`jnl`	Learning Differentially Private Probabilistic Models for Privacy-Preserving Image Generation. CoRR Bochao Liu, Shiming Ge, Pengju Wang, Liansheng Zhuang, Tongliang Liu
2023	J	`jnl`	Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning. CoRR Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu
2023	J	`jnl`	Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision. CoRR Yuhao Wu, Xiaobo Xia, Jun Yu, Bo Han, Gang Niu, Masashi Sugiyama, Tongliang Liu
2023	J	`jnl`	Model2Scene: Learning 3D Scene Representation via Contrastive Language-CAD Models Pre-training. CoRR Runnan Chen, Xinge Zhu, Nenglun Chen, Dawei Wang, Wei Li, Yuexin Ma, Ruigang Yang, Tongliang Liu, Wenping Wang
2023	A*	`conf`	Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning. ICLR Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu
2023	A*	`conf`	Mosaic Representation Learning for Self-supervised Visual Pre-training. ICLR Zhaoqing Wang, Ziyu Chen, Yaqian Li, Yandong Guo, Jun Yu, Mingming Gong, Tongliang Liu
2023	J	`jnl`	Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm. CoRR Shikun Li, Xiaobo Xia, Hansong Zhang, Shiming Ge, Tongliang Liu
2023	A*	`conf`	Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering. ICCV Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong
2023	J	`jnl`	Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering. CoRR Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong
2023	J	`jnl`	Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions. Trans. Mach. Learn. Res. Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang
2023	J	`jnl`	On Exploring Node-feature and Graph-structure Diversities for Node Drop Graph Pooling. CoRR Chuang Liu, Yibing Zhan, Baosheng Yu, Liu Liu, Bo Du, Wenbin Hu, Tongliang Liu
2023	J	`jnl`	On exploring node-feature and graph-structure diversities for node drop graph pooling. Neural Networks Chuang Liu, Yibing Zhan, Baosheng Yu, Liu Liu, Bo Du, Wenbin Hu, Tongliang Liu
2023	J	`jnl`	On the Onset of Robust Overfitting in Adversarial Training. CoRR Chaojian Yu, Xiaolong Shi, Jun Yu, Bo Han, Tongliang Liu
2023	J	`jnl`	On the Over-Memorization During Natural, Robust and Catastrophic Overfitting. CoRR Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu
2023	J	`jnl`	One Shot Learning as Instruction Data Prospector for Large Language Models. CoRR Yunshui Li, Binyuan Hui, Xiaobo Xia, Jiaxi Yang, Min Yang, Lei Zhang, Shuzheng Si, Junhao Liu, Tongliang Liu, Fei Huang, Yongbin Li
2023	A*	`conf`	Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. NeurIPS Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023	J	`jnl`	Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. CoRR Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023	A*	`conf`	Out-of-distribution Detection with Implicit Outlier Transformation. ICLR Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han
2023	J	`jnl`	Out-of-distribution Detection with Implicit Outlier Transformation. CoRR Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han
2023	A*	`conf`	PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels. ICCV Huaxi Huang, Hui Kang, Sheng Liu, Olivier Salvado, Thierry Rakotoarivelo, Dadong Wang, Tongliang Liu
2023	A*	`conf`	PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. ACM Multimedia Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao
2023	J	`jnl`	PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions. CoRR Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, Dacheng Tao
2023	A*	`conf`	Phase-aware Adversarial Defense for Improving Adversarial Robustness. ICML Dawei Zhou, Nannan Wang, Heng Yang, Xinbo Gao, Tongliang Liu
2023	A*	`conf`	Point-Query Quadtree for Crowd Counting, Localization, and More. ICCV Chengxin Liu, Hao Lu, Zhiguo Cao, Tongliang Liu
2023	J	`jnl`	Point-Query Quadtree for Crowd Counting, Localization, and More. CoRR Chengxin Liu, Hao Lu, Zhiguo Cao, Tongliang Liu
2023	J	`jnl`	Quantization Aware Attack: Enhancing the Transferability of Adversarial Attacks across Target Models with Different Quantization Bitwidths. CoRR Yulong Yang, Chenhao Lin, Qian Li, Chao Shen, Dawei Zhou, Nannan Wang, Tongliang Liu
2023	J	`jnl`	Recent Advances for Quantum Neural Networks in Generative Learning. IEEE Trans. Pattern Anal. Mach. Intell. Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, Dacheng Tao
2023	J	`jnl`	Regularly Truncated M-estimators for Learning with Noisy Labels. CoRR Xiaobo Xia, Pengqian Lu, Chen Gong, Bo Han, Jun Yu, Jun Yu, Tongliang Liu
2023	J	`jnl`	Relation-Aware Fine-Grained Reasoning Network for Textbook Question Answering. IEEE Trans. Neural Networks Learn. Syst. Jie Ma, Jun Liu, Yaxian Wang, Junjun Li, Tongliang Liu
2023	A*	`conf`	Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization. CVPR Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
2023	J	`jnl`	Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization. CoRR Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu
2023	J	`jnl`	ShadowNet for Data-Centric Quantum System Learning. CoRR Yuxuan Du, Yibo Yang, Tongliang Liu, Zhouchen Lin, Bernard Ghanem, Dacheng Tao
2023	A*	`conf`	Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping. NeurIPS Yingbin Bai, Zhongyi Han, Erkun Yang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu
2023	A*	`conf`	Symmetric Pruning in Quantum Neural Networks. ICLR Xinbiao Wang, Junyu Liu, Tongliang Liu, Yong Luo, Yuxuan Du, Dacheng Tao
2023	J	`jnl`	Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer. CoRR Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Tianshuo Xu, Xiaoshuai Sun, Tongliang Liu, Rongrong Ji, Dacheng Tao
2023	A*	`conf`	Towards Label-free Scene Understanding by Vision Foundation Models. NeurIPS Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge Zhu, Yuexin Ma, Tongliang Liu, Wenping Wang
2023	J	`jnl`	Towards Label-free Scene Understanding by Vision Foundation Models. CoRR Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge Zhu, Yuexin Ma, Tongliang Liu, Wenping Wang
2023	J	`jnl`	Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds. CoRR Shikun Li, Xiaobo Xia, Jiankang Deng, Shiming Ge, Tongliang Liu
2023	J	`jnl`	Trustable Co-Label Learning From Multiple Noisy Annotators. IEEE Trans. Multim. Shikun Li, Tongliang Liu, Jiyong Tan, Dan Zeng, Shiming Ge
2023	J	`jnl`	Type-I Generative Adversarial Attack. IEEE Trans. Dependable Secur. Comput. Shenghong He, Ruxin Wang, Tongliang Liu, Chao Yi, Xin Jin, Renyang Liu, Wei Zhou
2023	J	`jnl`	Understanding How Pretraining Regularizes Deep Learning Algorithms. IEEE Trans. Neural Networks Learn. Syst. Yu Yao, Baosheng Yu, Chen Gong, Tongliang Liu
2023	A*	`conf`	Unicom: Universal and Compact Representation Learning for Image Retrieval. ICLR Xiang An, Jiankang Deng, Kaicheng Yang, Jaiwei Li, Ziyong Feng, Jia Guo, Jing Yang, Tongliang Liu
2023	J	`jnl`	Unicom: Universal and Compact Representation Learning for Image Retrieval. CoRR Xiang An, Jiankang Deng, Kaicheng Yang, Jaiwei Li, Ziyong Feng, Jia Guo, Jing Yang, Tongliang Liu
2023	A*	`conf`	Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability. ICML Jianing Zhu, Hengzhuang Li, Jiangchao Yao, Tongliang Liu, Jianliang Xu, Bo Han
2023	J	`jnl`	Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability. CoRR Jianing Zhu, Hengzhuang Li, Jiangchao Yao, Tongliang Liu, Jianliang Xu, Bo Han
2023	J	`jnl`	Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels. CoRR Hui Kang, Sheng Liu, Huaxi Huang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu
2023	A*	`conf`	Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu
2023	J	`jnl`	Why can neural language models solve next-word prediction? A mathematical perspective. CoRR Vinoth Nandakumar, Peng Mi, Tongliang Liu
2023	J	`jnl`	Why do CNNs excel at feature extraction? A mathematical explanation. CoRR Vinoth Nandakumar, Arush Tagade, Tongliang Liu
2023	J	`jnl`	Winning Prize Comes from Losing Tickets: Improve Invariant Learning by Exploring Variant Parameters for Out-of-Distribution Generalization. CoRR Zhuo Huang, Muyang Li, Li Shen, Jun Yu, Chen Gong, Bo Han, Tongliang Liu
2022	J	`jnl`	A Machine Learning Approach for Predicting Human Preference for Graph Layouts. J. Graph Algorithms Appl. Shijun Cai, Seok-Hee Hong, Jialiang Shen, Tongliang Liu
2022	J	`jnl`	A machine learning approach for predicting human shortest path task performance. Vis. Informatics Shijun Cai, Seok-Hee Hong, Xiaobo Xia, Tongliang Liu, Weidong Huang
2022	A*	`conf`	Adversarial Robustness Through the Lens of Causality. ICLR Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
2022	A*	`conf`	Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks. NeurIPS Jianan Zhou, Jianing Zhu, Jingfeng Zhang, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama
2022	J	`jnl`	Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks. CoRR Jianan Zhou, Jianing Zhu, Jingfeng Zhang, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama
2022	A*	`conf`	Bilateral Dependency Optimization: Defending Against Model-inversion Attacks. KDD Xiong Peng, Feng Liu, Jingfeng Zhang, Long Lan, Junjie Ye, Tongliang Liu, Bo Han
2022	J	`jnl`	Bilateral Dependency Optimization: Defending Against Model-inversion Attacks. CoRR Xiong Peng, Feng Liu, Jingfen Zhang, Long Lan, Junjie Ye, Tongliang Liu, Bo Han
2022	J	`jnl`	Bridging the Gap Between Few-Shot and Many-Shot Learning via Distribution Calibration. IEEE Trans. Pattern Anal. Mach. Intell. Shuo Yang, Songhua Wu, Tongliang Liu, Min Xu
2022	J	`jnl`	COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment. Pattern Recognit. Guoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, Xiuying Wang
2022	A*	`conf`	CRIS: CLIP-Driven Referring Image Segmentation. CVPR Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, Tongliang Liu
2022	A*	`conf`	Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization. NeurIPS De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu
2022	A*	`conf`	Counterfactual Fairness with Partially Known Causal Graph. NeurIPS Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong
2022	J	`jnl`	Counterfactual Fairness with Partially Known Causal Graph. CoRR Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong
2022	J	`jnl`	DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting. CoRR Maoyuan Ye, Jing Zhang, Shanshan Zhao, Juhua Liu, Tongliang Liu, Bo Du, Dacheng Tao
2022	J	`jnl`	Do We Need to Penalize Variance of Losses for Learning with Label Noise? CoRR Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu, Bo Han, Mingming Gong, Tongliang Liu
2022	A*	`conf`	Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network. ICML Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2022	A*	`conf`	Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning. NeurIPS Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu
2022	A*	`conf`	Exploiting Class Activation Value for Partial-Label Learning. ICLR Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama
2022	J	`jnl`	Exploring Language Hierarchy for Video Grounding. IEEE Trans. Image Process. Xinpeng Ding, Nannan Wang, Shiwei Zhang, Ziyuan Huang, Xiaomeng Li, Mingqian Tang, Tongliang Liu, Xinbo Gao
2022	A*	`conf`	Exploring Set Similarity for Dense Self-supervised Representation Learning. CVPR Zhaoqing Wang, Qiang Li, Guoxin Zhang, Pengfei Wan, Wen Zheng, Nannan Wang, Mingming Gong, Tongliang Liu
2022	—	`conf`	Fair Classification with Instance-dependent Label Noise. CLeaR Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu
2022	J	`jnl`	Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities. CoRR Chuang Liu, Yibing Zhan, Chang Li, Bo Du, Jia Wu, Wenbin Hu, Tongliang Liu, Dacheng Tao
2022	J	`jnl`	Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. CoRR Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu
2022	J	`jnl`	Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. Xu Yang, Cheng Deng, Tongliang Liu, Dacheng Tao
2022	J	`jnl`	Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations. CoRR Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao
2022	A*	`conf`	Improving Adversarial Robustness via Mutual Information Estimation. ICML Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang, Yibing Zhan, Tongliang Liu
2022	J	`jnl`	Improving Adversarial Robustness via Mutual Information Estimation. CoRR Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang, Yibing Zhan, Tongliang Liu
2022	J	`jnl`	Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation. IEEE Trans. Medical Imaging Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Quan Zhou, Tongliang Liu, Zongyuan Ge
2022	—	`conf`	Improving Supervised Learning in Conversational Analysis through Reusing Preprocessing Data as Auxiliary Supervisors. ICMI Companion Joshua Y. Kim, Tongliang Liu, Kalina Yacef
2022	A*	`conf`	Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation. CVPR De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama
2022	J	`jnl`	Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation. CoRR De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama
2022	J	`jnl`	Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation. IEEE Trans. Pattern Anal. Mach. Intell. Chen Gong, Qizhou Wang, Tongliang Liu, Bo Han, Jane You, Jian Yang, Dacheng Tao
2022	J	`jnl`	Invariance Principle Meets Out-of-Distribution Generalization on Graphs. CoRR Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
2022	A*	`conf`	Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC. CVPR Xiang An, Jiankang Deng, Jia Guo, Ziyong Feng, Xuhan Zhu, Jing Yang, Tongliang Liu
2022	J	`jnl`	Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC. CoRR Xiang An, Jiankang Deng, Jia Guo, Ziyong Feng, Xuhan Zhu, Jing Yang, Tongliang Liu
2022	J	`jnl`	LR-SVM+: Learning Using Privileged Information with Noisy Labels. IEEE Trans. Multim. Zhengning Wu, Xiaobo Xia, Ruxin Wang, Jiatong Li, Jun Yu, Yinian Mao, Tongliang Liu
2022	J	`jnl`	Label Propagated Nonnegative Matrix Factorization for Clustering. IEEE Trans. Knowl. Data Eng. Long Lan, Tongliang Liu, Xiang Zhang, Chuanfu Xu, Zhigang Luo
2022	J	`jnl`	Laplacian Welsch Regularization for Robust Semisupervised Learning. IEEE Trans. Cybern. Jingchen Ke, Chen Gong, Tongliang Liu, Lin Zhao, Jian Yang, Dacheng Tao
2022	A*	`conf`	Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. NeurIPS Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
2022	A	`conf`	Learning and Mining with Noisy Labels. CIKM Masashi Sugiyama, Tongliang Liu, Bo Han, Yang Liu, Gang Niu
2022	J	`jnl`	Learning from Noisy Pairwise Similarity and Unlabeled Data. J. Mach. Learn. Res. Songhua Wu, Tongliang Liu, Bo Han, Jun Yu, Gang Niu, Masashi Sugiyama
2022	A*	`conf`	Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. ICLR Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
2022	—	`conf`	MAPS: a dataset for semantic profiling and analysis of Android applications. MobiArch Amirmohammad Pasdar, Young Choon Lee, Seok-Hee Hong, Tongliang Liu
2022	J	`jnl`	MSR: Making Self-supervised learning Robust to Aggressive Augmentations. CoRR Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han, Cheng Deng, Dadong Wang, Tongliang Liu
2022	A*	`conf`	Meta Clustering Learning for Large-scale Unsupervised Person Re-identification. ACM Multimedia Xin Jin, Tianyu He, Xu Shen, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
2022	A*	`conf`	Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. ICLR Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
2022	A*	`conf`	MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. NeurIPS Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell
2022	J	`jnl`	MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. CoRR Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell
2022	A*	`conf`	Modeling Adversarial Noise for Adversarial Training. ICML Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu
2022	J	`jnl`	Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos. CoRR Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu
2022	A*	`conf`	Mutual Quantization for Cross-Modal Search with Noisy Labels. CVPR Erkun Yang, Dongren Yao, Tongliang Liu, Cheng Deng
2022	J	`jnl`	NoiLin: Improving adversarial training and correcting stereotype of noisy labels. Trans. Mach. Learn. Res. Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama
2022	C	`conf`	Nonlinear Multi-Model Reuse. MMSP Yong Luo, Ling-Yu Duan, Yan Bai, Tongliang Liu, Yihang Lou, Yonggang Wen
2022	J	`jnl`	On the Rates of Convergence From Surrogate Risk Minimizers to the Bayes Optimal Classifier. IEEE Trans. Neural Networks Learn. Syst. Jingwei Zhang, Tongliang Liu, Dacheng Tao
2022	A*	`conf`	Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE. NeurIPS Yewen Li, Chaojie Wang, Xiaobo Xia, Tongliang Liu, Xin Miao, Bo An
2022	J	`jnl`	PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels. CoRR Huaxi Huang, Hui Kang, Sheng Liu, Olivier Salvado, Thierry Rakotoarivelo, Dadong Wang, Tongliang Liu
2022	A*	`conf`	Pluralistic Image Completion with Gaussian Mixture Models. NeurIPS Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu
2022	J	`jnl`	Pluralistic Image Completion with Probabilistic Mixture-of-Experts. CoRR Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu
2022	J	`jnl`	Quantum Differentially Private Sparse Regression Learning. IEEE Trans. Inf. Theory Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao
2022	A*	`conf`	RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning. NeurIPS Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han, Cheng Deng, Dadong Wang, Tongliang Liu
2022	J	`jnl`	Recent Advances for Quantum Neural Networks in Generative Learning. CoRR Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, Dacheng Tao
2022	A*	`conf`	Reliable Adversarial Distillation with Unreliable Teachers. ICLR Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang
2022	A*	`conf`	Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. ICLR Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao
2022	A*	`conf`	Robust Weight Perturbation for Adversarial Training. IJCAI Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Bo Du, Tongliang Liu
2022	J	`jnl`	Robust Weight Perturbation for Adversarial Training. CoRR Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Bo Du, Tongliang Liu
2022	A*	`conf`	Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. ICLR Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
2022	A*	`conf`	Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data. KDD Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu
2022	A*	`conf`	Selective-Supervised Contrastive Learning with Noisy Labels. CVPR Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu
2022	J	`jnl`	Selective-Supervised Contrastive Learning with Noisy Labels. CoRR Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu
2022	A*	`conf`	SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation. CVPR Xiaoqing Guo, Jie Liu, Tongliang Liu, Yixuan Yuan
2022	J	`jnl`	SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation. CoRR Xiaoqing Guo, Jie Liu, Tongliang Liu, Yixuan Yuan
2022	J	`jnl`	Strength-Adaptive Adversarial Training. CoRR Chaojian Yu, Dawei Zhou, Li Shen, Jun Yu, Bo Han, Mingming Gong, Nannan Wang, Tongliang Liu
2022	J	`jnl`	Symmetric Pruning in Quantum Neural Networks. CoRR Xinbiao Wang, Junyu Liu, Tongliang Liu, Yong Luo, Yuxuan Du, Dacheng Tao
2022	J	`jnl`	TWGAN: Twin Discriminator Generative Adversarial Networks. IEEE Trans. Multim. Zhaoyu Zhang, Mengyan Li, Haonian Xie, Jun Yu, Tongliang Liu, Chang Wen Chen
2022	A*	`conf`	To Smooth or Not? When Label Smoothing Meets Noisy Labels. ICML Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama, Yang Liu
2022	A*	`conf`	Towards Lightweight Black-Box Attack Against Deep Neural Networks. NeurIPS Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
2022	J	`jnl`	Towards Lightweight Black-Box Attacks against Deep Neural Networks. CoRR Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
2022	B	`conf`	Train Me to Fight: Machine-Learning Based On-Device Malware Detection for Mobile Devices. CCGRID Amirmohammad Pasdar, Young Choon Lee, Tongliang Liu, Seok-Hee Hong
2022	J	`jnl`	Transferable Coupled Network for Zero-Shot Sketch-Based Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. Hao Wang, Cheng Deng, Tongliang Liu, Dacheng Tao
2022	J	`jnl`	Trustable Co-label Learning from Multiple Noisy Annotators. CoRR Shikun Li, Tongliang Liu, Jiyong Tan, Dan Zeng, Shiming Ge
2022	A*	`conf`	Understanding Robust Overfitting of Adversarial Training and Beyond. ICML Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu
2022	J	`jnl`	Understanding Robust Overfitting of Adversarial Training and Beyond. CoRR Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu
2022	A*	`conf`	Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. ICLR Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
2022	J	`jnl`	Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. CoRR Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
2022	—	`conf`	Unleashing the Potential of Adaptation Models via Go-getting Domain Labels. ECCV Workshops (8) Xin Jin, Tianyu He, Xu Shen, Songhua Wu, Tongliang Liu, Jingwen Ye, Xinchao Wang, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
2022	A*	`conf`	Watermarking for Out-of-distribution Detection. NeurIPS Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han
2022	J	`jnl`	Watermarking for Out-of-distribution Detection. CoRR Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han
2021	B	`conf`	A Machine Learning Approach for Predicting Human Preference for Graph Layouts PacificVis Shijun Cai, Seok-Hee Hong, Jialiang Shen, Tongliang Liu
2021	J	`jnl`	A Machine Learning Approach for Predicting Human Preference for Graph Layouts. CoRR Shijun Cai, Seok-Hee Hong, Jialiang Shen, Tongliang Liu
2021	A*	`conf`	A Second-Order Approach to Learning With Instance-Dependent Label Noise. CVPR Zhaowei Zhu, Tongliang Liu, Yang Liu
2021	J	`jnl`	A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection. Int. J. Comput. Vis. Zhe Chen, Wanli Ouyang, Tongliang Liu, Dacheng Tao
2021	J	`jnl`	Adversarial Robustness through the Lens of Causality. CoRR Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
2021	—	`conf`	Boosting Fairness for Masked Face Recognition. ICCVW Jun Yu, Xinlong Hao, Zeyu Cui, Peng He, Tongliang Liu
2021	J	`jnl`	CRIS: CLIP-Driven Referring Image Segmentation. CoRR Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, Tongliang Liu
2021	A*	`conf`	Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels. ICML Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
2021	A*	`conf`	Confidence Scores Make Instance-dependent Label-noise Learning Possible. ICML Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
2021	A*	`conf`	Confident Anchor-Induced Multi-Source Free Domain Adaptation. NeurIPS Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu
2021	J	`jnl`	Estimating Instance-dependent Label-noise Transition Matrix using DNNs. CoRR Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2021	J	`jnl`	Exploring Set Similarity for Dense Self-supervised Representation Learning. CoRR Zhaoqing Wang, Qiang Li, Guoxin Zhang, Pengfei Wan, Wen Zheng, Nannan Wang, Mingming Gong, Tongliang Liu
2021	J	`jnl`	Federated Causal Discovery. CoRR Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard D. Bondell
2021	J	`jnl`	HRSiam: High-Resolution Siamese Network, Towards Space-Borne Satellite Video Tracking. IEEE Trans. Image Process. Jia Shao, Bo Du, Chen Wu, Mingming Gong, Tongliang Liu
2021	J	`jnl`	Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation. CoRR Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Mehrtash Harandi, Tom Drummond, Tongliang Liu, Zongyuan Ge
2021	J	`jnl`	Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training. CoRR Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Jun Yu, Xiaoyu Wang, Tongliang Liu
2021	J	`jnl`	Instance Correction for Learning with Open-set Noisy Labels. CoRR Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
2021	A*	`conf`	Instance-dependent Label-noise Learning under a Structural Causal Model. NeurIPS Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang
2021	J	`jnl`	Instance-dependent Label-noise Learning under a Structural Causal Model. CoRR Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang
2021	J	`jnl`	KFC: An Efficient Framework for Semi-Supervised Temporal Action Localization. IEEE Trans. Image Process. Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu
2021	J	`jnl`	KRADA: Known-region-aware Domain Alignment for Open World Semantic Segmentation. CoRR Chenhong Zhou, Feng Liu, Chen Gong, Tongliang Liu, Bo Han, William Kwok-Wai Cheung
2021	J	`jnl`	Kernel Mean Estimation by Marginalized Corrupted Distributions. CoRR Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu
2021	A*	`conf`	Learning Diverse-Structured Networks for Adversarial Robustness. ICML Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama
2021	J	`jnl`	Learning Diverse-Structured Networks for Adversarial Robustness. CoRR Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama
2021	A*	`conf`	Learning with Group Noise. AAAI Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han
2021	J	`jnl`	Learning with Group Noise. CoRR Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han
2021	J	`jnl`	Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. CoRR Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
2021	J	`jnl`	Loss Decomposition and Centroid Estimation for Positive and Unlabeled Learning. IEEE Trans. Pattern Anal. Mach. Intell. Chen Gong, Hong Shi, Tongliang Liu, Chuang Zhang, Jian Yang, Dacheng Tao
2021	A*	`conf`	Maximum Mean Discrepancy Test is Aware of Adversarial Attacks. ICML Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama
2021	A*	`conf`	Me-Momentum: Extracting Hard Confident Examples from Noisily Labeled Data. ICCV Yingbin Bai, Tongliang Liu
2021	J	`jnl`	Meta Clustering Learning for Large-scale Unsupervised Person Re-identification. CoRR Xin Jin, Tianyu He, Zhiheng Yin, Xu Shen, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
2021	J	`jnl`	Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. CoRR Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Gang Niu, Bo Han
2021	J	`jnl`	Modelling Adversarial Noise for Adversarial Defense. CoRR Dawei Zhou, Nannan Wang, Tongliang Liu, Bo Han
2021	J	`jnl`	NoiLIn: Do Noisy Labels Always Hurt Adversarial Training? CoRR Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama
2021	J	`jnl`	Orthogonal Deep Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Shuai Li, Kui Jia, Yuxin Wen, Tongliang Liu, Dacheng Tao
2021	J	`jnl`	PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels. CoRR Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Junzhou Huang
2021	A*	`conf`	Probabilistic Margins for Instance Reweighting in Adversarial Training. NeurIPS Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
2021	J	`jnl`	Probabilistic Margins for Instance Reweighting in Adversarial Training. CoRR Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
2021	J	`jnl`	Provably End-to-end Label-Noise Learning without Anchor Points. CoRR Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama
2021	A*	`conf`	Provably End-to-end Label-noise Learning without Anchor Points. ICML Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama
2021	—	`conf`	Relational Subsets Knowledge Distillation for Long-Tailed Retinal Diseases Recognition. MICCAI (8) Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, Zongyuan Ge
2021	J	`jnl`	Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition. CoRR Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, Zongyuan Ge
2021	J	`jnl`	Reliable Adversarial Distillation with Unreliable Teachers. CoRR Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang
2021	A*	`conf`	Removing Adversarial Noise in Class Activation Feature Space. ICCV Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu
2021	J	`jnl`	Removing Adversarial Noise in Class Activation Feature Space. CoRR Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu
2021	A*	`conf`	Revisiting Knowledge Distillation: An Inheritance and Exploration Framework. CVPR Zhen Huang, Xu Shen, Jun Xing, Tongliang Liu, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua
2021	J	`jnl`	Revisiting Knowledge Distillation: An Inheritance and Exploration Framework. CoRR Zhen Huang, Xu Shen, Jun Xing, Tongliang Liu, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua
2021	A	`conf`	Robust Dual Recurrent Neural Networks for Financial Time Series Prediction. SDM Jiayu He, Matloob Khushi, Nguyen Hoang Tran, Tongliang Liu
2021	A*	`conf`	Robust early-learning: Hindering the memorization of noisy labels. ICLR Xiaobo Xia, Tongliang Liu, Bo Han, Chen Gong, Nannan Wang, Zongyuan Ge, Yi Chang
2021	J	`jnl`	Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. CoRR Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
2021	A*	`conf`	TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation. NeurIPS Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, William K. Cheung, James T. Kwok
2021	J	`jnl`	TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation. CoRR Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, William K. Cheung, James T. Kwok
2021	A*	`conf`	Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model. AAAI Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong
2021	J	`jnl`	Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model. CoRR Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong
2021	A*	`conf`	Towards Defending against Adversarial Examples via Attack-Invariant Features. ICML Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
2021	J	`jnl`	Towards Defending against Adversarial Examples via Attack-Invariant Features. CoRR Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
2021	J	`jnl`	Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors. CoRR Joshua Yee Kim, Tongliang Liu, Kalina Yacef
2021	J	`jnl`	Understanding (Generalized) Label Smoothing when Learning with Noisy Labels. CoRR Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu
2021	A*	`conf`	Understanding and Improving Early Stopping for Learning with Noisy Labels. NeurIPS Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li, Yinian Mao, Gang Niu, Tongliang Liu
2021	J	`jnl`	Understanding and Improving Early Stopping for Learning with Noisy Labels. CoRR Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li, Yinian Mao, Gang Niu, Tongliang Liu
2021	J	`jnl`	Understanding the Interaction of Adversarial Training with Noisy Labels. CoRR Jianing Zhu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Hongxia Yang, Mohan S. Kankanhalli, Masashi Sugiyama
2021	C	`conf`	Vecnet: A Spectral and Multi-Scale Spatial Fusion Deep Network for Pixel-Level Cloud Type Classification in Himawari-8 Imagery. IGARSS Zhaoqing Wang, Xiangyu Kong, Zhanbei Cui, Ming Wu, Chuang Zhang, Mingming Gong, Tongliang Liu
2020	J	`jnl`	A Second-Order Approach to Learning with Instance-Dependent Label Noise. CoRR Zhaowei Zhu, Tongliang Liu, Yang Liu
2020	J	`jnl`	A Survey of Label-noise Representation Learning: Past, Present and Future. CoRR Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama
2020	J	`jnl`	Absent Multiple Kernel Learning Algorithms. IEEE Trans. Pattern Anal. Mach. Intell. Xinwang Liu, Lei Wang, Xinzhong Zhu, Miaomiao Li, En Zhu, Tongliang Liu, Li Liu, Yong Dou, Jianping Yin
2020	J	`jnl`	Adversarial Examples for Hamming Space Search. IEEE Trans. Cybern. Erkun Yang, Tongliang Liu, Cheng Deng, Dacheng Tao
2020	J	`jnl`	COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19. CoRR Guoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, Xiuying Wang
2020	J	`jnl`	Class2Simi: A New Perspective on Learning with Label Noise. CoRR Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
2020	J	`jnl`	Confidence Scores Make Instance-dependent Label-noise Learning Possible. CoRR Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
2020	A*	`conf`	Deep Heterogeneous Multi-Task Metric Learning for Visual Recognition and Retrieval. ACM Multimedia Shikang Gan, Yong Luo, Yonggang Wen, Tongliang Liu, Han Hu
2020	A*	`conf`	Diversified Bayesian Nonnegative Matrix Factorization. AAAI Maoying Qiao, Jun Yu, Tongliang Liu, Xinchao Wang, Dacheng Tao
2020	A*	`conf`	Domain Generalization via Entropy Regularization. NeurIPS Shanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, Dacheng Tao
2020	A*	`conf`	Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. NeurIPS Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama
2020	J	`jnl`	Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. CoRR Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama
2020	A*	`conf`	Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks. ICML Yonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian
2020	J	`jnl`	Experimental Quantum Generative Adversarial Networks for Image Generation. CoRR Heliang Huang, Yuxuan Du, Ming Gong, Youwei Zhao, Yulin Wu, Chaoyue Wang, Shaowei Li, Futian Liang, Jin Lin, Yu Xu, Rui Yang, Tongliang Liu, Min-Hsiu Hsieh, Hui Deng, Hao Rong, Cheng-Zhi Peng, Chao-yang Lu, Yu-Ao Chen, Dacheng Tao, Xiaobo Zhu, Jian-Wei Pan
2020	J	`jnl`	Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels. CoRR Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao
2020	A*	`conf`	Generative-Discriminative Complementary Learning. AAAI Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich
2020	J	`jnl`	Group Feedback Capsule Network. IEEE Trans. Image Process. Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu
2020	J	`jnl`	Harnessing Side Information for Classification Under Label Noise. IEEE Trans. Neural Networks Learn. Syst. Yang Wei, Chen Gong, Shuo Chen, Tongliang Liu, Jian Yang, Dacheng Tao
2020	A*	`conf`	LTF: A Label Transformation Framework for Correcting Label Shift. ICML Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao
2020	A*	`conf`	Label-Noise Robust Domain Adaptation. ICML Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao
2020	A*	`conf`	Learning with Bounded Instance and Label-dependent Label Noise. ICML Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao
2020	J	`jnl`	Maximum Mean Discrepancy is Aware of Adversarial Attacks. CoRR Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama
2020	J	`jnl`	Multi-Class Classification from Noisy-Similarity-Labeled Data. CoRR Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
2020	J	`jnl`	Multiple Kernel $k$k-Means with Incomplete Kernels. IEEE Trans. Pattern Anal. Mach. Intell. Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Lei Wang, En Zhu, Tongliang Liu, Marius Kloft, Dinggang Shen, Jianping Yin, Wen Gao
2020	A*	`conf`	Part-dependent Label Noise: Towards Instance-dependent Label Noise. NeurIPS Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama
2020	J	`jnl`	Parts-dependent Label Noise: Towards Instance-dependent Label Noise. CoRR Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama
2020	J	`jnl`	Quantum differentially private sparse regression learning. CoRR Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao
2020	J	`jnl`	Quantum noise protects quantum classifiers against adversaries. CoRR Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao, Nana Liu
2020	J	`jnl`	Repulsive Mixture Models of Exponential Family PCA for Clustering. CoRR Maoying Qiao, Tongliang Liu, Jun Yu, Wei Bian, Dacheng Tao
2020	—	`conf`	Sub-center ArcFace: Boosting Face Recognition by Large-Scale Noisy Web Faces. ECCV (11) Jiankang Deng, Jia Guo, Tongliang Liu, Mingming Gong, Stefanos Zafeiriou
2020	J	`jnl`	Towards Efficient Front-End Visual Sensing for Digital Retina: A Model-Centric Paradigm. IEEE Trans. Multim. Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao
2020	J	`jnl`	Towards Mixture Proportion Estimation without Irreducibility. CoRR Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao
2020	J	`jnl`	Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search. IEEE Trans. Neural Networks Learn. Syst. Cheng Deng, Erkun Yang, Tongliang Liu, Dacheng Tao
2020	J	`jnl`	Weakly Supervised Temporal Action Localization with Segment-Level Labels. CoRR Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu
2020	J	`jnl`	Why ResNet Works? Residuals Generalize. IEEE Trans. Neural Networks Learn. Syst. Fengxiang He, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	A Quantum-inspired Algorithm for General Minimum Conical Hull Problems. CoRR Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	A Regularization Approach for Instance-Based Superset Label Learning. CoRR Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao
2019	J	`jnl`	A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection. CoRR Zhe Chen, Wanli Ouyang, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	Adaptive Morphological Reconstruction for Seeded Image Segmentation. CoRR Tao Lei, Xiaohong Jia, Tongliang Liu, Shigang Liu, Hongying Meng, Asoke K. Nandi
2019	J	`jnl`	Adaptive Morphological Reconstruction for Seeded Image Segmentation. IEEE Trans. Image Process. Tao Lei, Xiaohong Jia, Tongliang Liu, Shigang Liu, Hongying Meng, Asoke K. Nandi
2019	J	`jnl`	Advances in data representation and learning for pattern analysis. Neurocomputing C. L. Philip Chen, Xinge You, Xinbo Gao, Tongliang Liu, Fionn Murtagh, Weifeng Liu
2019	A*	`conf`	Are Anchor Points Really Indispensable in Label-Noise Learning? NeurIPS Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama
2019	J	`jnl`	Are Anchor Points Really Indispensable in Label-Noise Learning? CoRR Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama
2019	J	`jnl`	Continuous Dropout. CoRR Xu Shen, Xinmei Tian, Tongliang Liu, Fang Xu, Dacheng Tao
2019	A*	`conf`	Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence. NeurIPS Fengxiang He, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	Decomposition-Based Transfer Distance Metric Learning for Image Classification. CoRR Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu
2019	A*	`conf`	DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs. CVPR Erkun Yang, Tongliang Liu, Cheng Deng, Wei Liu, Dacheng Tao
2019	J	`jnl`	DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs. CoRR Erkun Yang, Tongliang Liu, Cheng Deng, Wei Liu, Dacheng Tao
2019	J	`jnl`	Eigenfunction-Based Multitask Learning in a Reproducing Kernel Hilbert Space. IEEE Trans. Neural Networks Learn. Syst. Xinmei Tian, Ya Li, Tongliang Liu, Xinchao Wang, Dacheng Tao
2019	J	`jnl`	Fast Supervised Discrete Hashing. CoRR Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan
2019	J	`jnl`	Generative-Discriminative Complementary Learning. CoRR Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich
2019	J	`jnl`	Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning. IEEE Trans. Neural Networks Learn. Syst. Chen Gong, Tongliang Liu, Jian Yang, Dacheng Tao
2019	J	`jnl`	Multi-View Matrix Completion for Multi-Label Image Classification. CoRR Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu
2019	J	`jnl`	On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning. CoRR Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	Orthogonal Deep Neural Networks. CoRR Kui Jia, Shuai Li, Yuxin Wen, Tongliang Liu, Dacheng Tao
2019	A*	`conf`	Positive and Unlabeled Learning with Label Disambiguation. IJCAI Chuang Zhang, Dexin Ren, Tongliang Liu, Jian Yang, Chen Gong
2019	J	`jnl`	Robust Angular Local Descriptor Learning. CoRR Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang
2019	—	`conf`	Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer. INNSBDDL Yasutaka Furusho, Tongliang Liu, Kazushi Ikeda
2019	J	`jnl`	Supervised Discrete Hashing with Relaxation. CoRR Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan
2019	A	`conf`	Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm. ICME Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao
2019	J	`jnl`	Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm. CoRR Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao
2019	J	`jnl`	Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain. CoRR Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	Transferring Knowledge Fragments for Learning Distance Metric from a Heterogeneous Domain. IEEE Trans. Pattern Anal. Mach. Intell. Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	Truncated Cauchy Non-Negative Matrix Factorization. IEEE Trans. Pattern Anal. Mach. Intell. Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, Dacheng Tao, Larry S. Davis
2019	J	`jnl`	Truncated Cauchy Non-negative Matrix Factorization. CoRR Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, Dacheng Tao, Larry S. Davis
2019	J	`jnl`	Unsupervised Semantic-Preserving Adversarial Hashing for Image Search. IEEE Trans. Image Process. Cheng Deng, Erkun Yang, Tongliang Liu, Jie Li, Wei Liu, Dacheng Tao
2019	J	`jnl`	Where is the Bottleneck of Adversarial Learning with Unlabeled Data? CoRR Jingfeng Zhang, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
2019	J	`jnl`	Why ResNet Works? Residuals Generalize. CoRR Fengxiang He, Tongliang Liu, Dacheng Tao
2019	J	`jnl`	dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs. CoRR Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, Dacheng Tao
2018	J	`jnl`	A Regularization Approach for Instance-Based Superset Label Learning. IEEE Trans. Cybern. Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao
2018	A*	`conf`	An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption. CVPR Xiyu Yu, Tongliang Liu, Mingming Gong, Kayhan Batmanghelich, Dacheng Tao
2018	J	`jnl`	An Information-Theoretic View for Deep Learning. CoRR Jingwei Zhang, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	An Optimal Transport View on Generalization. CoRR Jingwei Zhang, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	Continuous Dropout. IEEE Trans. Neural Networks Learn. Syst. Xu Shen, Xinmei Tian, Tongliang Liu, Fang Xu, Dacheng Tao
2018	—	`conf`	Correcting the Triplet Selection Bias for Triplet Loss. ECCV (6) Baosheng Yu, Tongliang Liu, Mingming Gong, Changxing Ding, Dacheng Tao
2018	J	`jnl`	Deep Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks. IEEE Trans. Image Process. Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, Dacheng Tao
2018	—	`conf`	Deep Domain Generalization via Conditional Invariant Adversarial Networks. ECCV (15) Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, Dacheng Tao
2018	J	`jnl`	Domain Generalization via Conditional Invariant Representation. CoRR Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, Dacheng Tao
2018	A*	`conf`	Domain Generalization via Conditional Invariant Representations. AAAI Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	Fast Supervised Discrete Hashing. IEEE Trans. Pattern Anal. Mach. Intell. Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan
2018	J	`jnl`	Implementable Quantum Classifier for Nonlinear Data. CoRR Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	Instance-Dependent PU Learning by Bayesian Optimal Relabeling. CoRR Fengxiang He, Tongliang Liu, Geoffrey I. Webb, Dacheng Tao
2018	—	`conf`	Learning with Biased Complementary Labels. ECCV (1) Xiyu Yu, Tongliang Liu, Mingming Gong, Dacheng Tao
2018	J	`jnl`	Multiclass Learning With Partially Corrupted Labels. IEEE Trans. Neural Networks Learn. Syst. Ruxin Wang, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning. IEEE Trans. Neural Networks Learn. Syst. Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao
2018	J	`jnl`	On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes Optimal Classifier. CoRR Jingwei Zhang, Tongliang Liu, Dacheng Tao
2018	A*	`conf`	Online Heterogeneous Transfer Metric Learning. IJCAI Yong Luo, Tongliang Liu, Yonggang Wen, Dacheng Tao
2018	A*	`conf`	Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization. IJCAI Yuxuan Du, Tongliang Liu, Yinan Li, Runyao Duan, Dacheng Tao
2018	A*	`conf`	Reliable Multi-View Clustering. AAAI Hong Tao, Chenping Hou, Xinwang Liu, Tongliang Liu, Dongyun Yi, Jubo Zhu
2018	—	`conf`	Robust Angular Local Descriptor Learning. ACCV (5) Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang
2018	A*	`conf`	Semantic Structure-based Unsupervised Deep Hashing. IJCAI Erkun Yang, Cheng Deng, Tongliang Liu, Wei Liu, Dacheng Tao
2018	J	`jnl`	Supervised Discrete Hashing With Relaxation. IEEE Trans. Neural Networks Learn. Syst. Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan
2018	J	`jnl`	The Expressive Power of Parameterized Quantum Circuits. CoRR Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao
2017	J	`jnl`	Algorithm-Dependent Generalization Bounds for Multi-Task Learning. IEEE Trans. Pattern Anal. Mach. Intell. Tongliang Liu, Dacheng Tao, Mingli Song, Stephen J. Maybank
2017	A*	`conf`	Algorithmic Stability and Hypothesis Complexity. ICML Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao
2017	J	`jnl`	Algorithmic stability and hypothesis complexity. CoRR Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao
2017	J	`jnl`	Elastic Net Hypergraph Learning for Image Clustering and Semi-Supervised Classification. IEEE Trans. Image Process. Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, Dacheng Tao
2017	A*	`conf`	General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer. IJCAI Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao
2017	J	`jnl`	Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection. IEEE Trans. Geosci. Remote. Sens. Yuxiang Zhang, Bo Du, Liangpei Zhang, Tongliang Liu
2017	J	`jnl`	Large-Cone Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. Tongliang Liu, Mingming Gong, Dacheng Tao
2017	J	`jnl`	Learning with Biased Complementary Labels. CoRR Xiyu Yu, Tongliang Liu, Mingming Gong, Dacheng Tao
2017	J	`jnl`	Learning with Bounded Instance- and Label-dependent Label Noise. CoRR Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao
2017	A*	`conf`	On Compressing Deep Models by Low Rank and Sparse Decomposition. CVPR Xiyu Yu, Tongliang Liu, Xinchao Wang, Dacheng Tao
2017	J	`jnl`	Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence. IEEE Trans. Knowl. Data Eng. Hongfu Liu, Junjie Wu, Tongliang Liu, Dacheng Tao, Yun Fu
2017	A*	`conf`	Understanding How Feature Structure Transfers in Transfer Learning. IJCAI Tongliang Liu, Qiang Yang, Dacheng Tao
2017	J	`jnl`	dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs. IEEE Trans. Image Process. Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, Dacheng Tao
2016	J	`jnl`	Classification with Noisy Labels by Importance Reweighting. IEEE Trans. Pattern Anal. Mach. Intell. Tongliang Liu, Dacheng Tao
2016	J	`jnl`	Dimensionality-Dependent Generalization Bounds for Neural Comput. Tongliang Liu, Dacheng Tao, Dong Xu
2016	J	`jnl`	Dimensionality-Dependent Generalization Bounds for $k$-Dimensional Coding Schemes. CoRR Tongliang Liu, Dacheng Tao, Dong Xu
2016	A*	`conf`	Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. AAAI Hao Xiong, Tongliang Liu, Dacheng Tao
2016	A*	`conf`	Domain Adaptation with Conditional Transferable Components. ICML Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf
2016	J	`jnl`	Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing. IEEE Trans. Image Process. Hao Xiong, Tongliang Liu, Dacheng Tao, Heng Tao Shen
2016	J	`jnl`	Elastic Net Hypergraph Learning for Image Clustering and Semi-supervised Classification. CoRR Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, Dacheng Tao
2016	J	`jnl`	Local Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks. CoRR Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, Dacheng Tao
2016	J	`jnl`	Local Rademacher Complexity for Multi-Label Learning. IEEE Trans. Image Process. Chang Xu, Tongliang Liu, Dacheng Tao, Chao Xu
2016	J	`jnl`	On the Performance of Manhattan Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. Tongliang Liu, Dacheng Tao
2016	J	`jnl`	Representative Vector Machines: A Unified Framework for Classical Classifiers. IEEE Trans. Cybern. Jie Gui, Tongliang Liu, Dacheng Tao, Zhenan Sun, Tieniu Tan
2016	—	`—`	The complexity of algorithmic hypothesis class Tongliang Liu
2016	J	`jnl`	Video Face Editing Using Temporal-Spatial-Smooth Warping. ACM Trans. Intell. Syst. Technol. Xiaoyan Li, Tongliang Liu, Jiankang Deng, Dacheng Tao
2015	J	`jnl`	Deformed Graph Laplacian for Semisupervised Learning. IEEE Trans. Neural Networks Learn. Syst. Chen Gong, Tongliang Liu, Dacheng Tao, Keren Fu, Enmei Tu, Jie Yang
2015	A*	`conf`	Multi-Task Model and Feature Joint Learning. IJCAI Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao
2015	J	`jnl`	Multiview Matrix Completion for Multilabel Image Classification. IEEE Trans. Image Process. Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu
2015	J	`jnl`	No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model. IEEE Signal Process. Lett. Yanan Lu, Fengying Xie, Tongliang Liu, Zhiguo Jiang, Dacheng Tao
2015	A*	`conf`	Spectral Ensemble Clustering. KDD Hongfu Liu, Tongliang Liu, Junjie Wu, Dacheng Tao, Yun Fu
2014	J	`jnl`	Classification with Noisy Labels by Importance Reweighting. CoRR Tongliang Liu, Dacheng Tao
2014	J	`jnl`	Decomposition-Based Transfer Distance Metric Learning for Image Classification. IEEE Trans. Image Process. Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu
2014	A	`conf`	Learning relative features through adaptive pooling for image classification. ICME Ming Shao, Sheng Li, Tongliang Liu, Dacheng Tao, Thomas S. Huang, Yun Fu
2014	J	`jnl`	Local Rademacher Complexity for Multi-label Learning. CoRR Chang Xu, Tongliang Liu, Dacheng Tao, Chao Xu