Bo Han - RankMe

454 papers A* 162A 3B 1Journal 282Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models. CoRR Fengpeng Li, Kemou Li, Qizhou Wang, Bo Han, Jiantao Zhou
2026	J	`jnl`	Atom-Motif Contrastive Transformer for Molecular Property Prediction. ACM Trans. Intell. Syst. Technol. Wentao Yu, Shuo Chen, Chen Gong, Bo Han, Gang Niu, Masashi Sugiyama
2026	J	`jnl`	Beyond Raw Detection Scores: Markov-Informed Calibration for Boosting Machine-Generated Text Detection. CoRR Chenwang Wu, Yiu-ming Cheung, Shuhai Zhang, Bo Han, Defu Lian
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`	CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad. CoRR Yongqiang Chen, Chenxi Liu, Zhenhao Chen, Tongliang Liu, Bo Han, Kun Zhang
2026	J	`jnl`	Continuous Review and Timely Correction: Enhancing the Resistance to Noisy Labels via Self-Not-True and Class-Wise Distillation. IEEE Trans. Pattern Anal. Mach. Intell. Long Lan, Jingyi Wang, Xinghao Wu, Bo Han, Xinwang Liu
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`	FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients. CoRR Tian Wen, Zhiqin Yang, Yonggang Zhang, Xuefeng Jiang, Hao Peng, Yuwei Wang, 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	J	`jnl`	Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning. CoRR Wentao Yu, Sheng Wan, Shuo Chen, Bo Han, Chen Gong
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`	MeGU: Machine-Guided Unlearning with Target Feature Disentanglement. CoRR Haoyu Wang, Zhuo Huang, Xiaolong Wang, Bo Han, Zhiwei Lin, Tongliang Liu
2026	J	`jnl`	Multi-Agent Debate with Memory Masking. CoRR Hongduan Tian, Xiao Feng, Ziyuan Zhao, Xiangyu Zhu, Rolan Yan, Bo Han
2026	J	`jnl`	Per-parameter Task Arithmetic for Unlearning in Large Language Models. CoRR Chengyi Cai, Zesheng Ye, Jiangchao Yao, Jianzhong Qi, Bo Han, Xiaolu Zhang, Feng Liu, Jun Zhou
2026	J	`jnl`	Privileged information assisted learning from noisy correspondence. Neurocomputing Zihua Zhao, Tianjie Dai, Mengxi Chen, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
2026	J	`jnl`	Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoning. CoRR Xuan Li, Zhanke Zhou, Zongze Li, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
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	J	`jnl`	RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models. CoRR Xiao Feng, Bo Han, Zhanke Zhou, Jiaqi Fan, Jiangchao Yao, Ka Ho Li, Dahai Yu, Michael Kwok-Po Ng
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	A*	`conf`	Transferability of Adversarial Attacks in Video-based MLLMs: A Cross-modal Image-to-Video Approach. AAAI Linhao Huang, Xue Jiang, Zhiqiang Wang, Wentao Mo, Xi Xiao, Yongjie Yin, Bo Han, Feng Zheng
2026	J	`jnl`	TriSpec: Ternary Speculative Decoding via Lightweight Proxy Verification. CoRR Haoyun Jiang, Junqi He, Feng Hong, Xinlong Yang, Jianwei Zhang, Zheng Li, Zhengyang Zhuge, Zhiyong Chen, Bo Han, Junyang Lin, Jiangchao Yao
2026	J	`jnl`	Visual-Guided Key-Token Regularization for Multimodal Large Language Model Unlearning. CoRR Chengyi Cai, Zesheng Ye, Peike Li, Bo Han, Jianzhong Qi, Feng Liu
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
2025	J	`jnl`	A Definition of AGI. CoRR Dan Hendrycks, Dawn Song, Christian Szegedy, Honglak Lee, Yarin Gal, Erik Brynjolfsson, Sharon Li, Andy Zou, Lionel Levine, Bo Han, Jie Fu, Ziwei Liu, Jinwoo Shin, Kimin Lee, Mantas Mazeika, Long Phan, George Ingebretsen, Adam Khoja, Cihang Xie, Olawale Salaudeen, Matthias Hein, Kevin Zhao, Alexander Pan, David Duvenaud, Bo Li, Steve Omohundro, Gabriel Alfour, Max Tegmark, Kevin McGrew, Gary Marcus, Jaan Tallinn, Eric Schmidt, Yoshua Bengio
2025	A*	`conf`	A Lens into Interpretable Transformer Mistakes via Semantic Dependency. ICML Ruo-Jing Dong, Yu Yao, Bo Han, Tongliang Liu
2025	J	`jnl`	A Robust Co-Training Framework to Handle Noisy Labels for Remote Sensing Image Segmentation. IEEE Trans. Geosci. Remote. Sens. Mitsuyoshi Otsu, Jun Zhou, Bo Han, Arnon Accad, Shirui Pan
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	J	`jnl`	Accurate Forgetting for Heterogeneous Federated Continual Learning. CoRR Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama
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	A*	`conf`	Adaptive Localization of Knowledge Negation for Continual LLM Unlearning. ICML Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui, Wutong Xu, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
2025	J	`jnl`	Advancing Machine-Generated Text Detection from an Easy to Hard Supervision Perspective. CoRR Chenwang Wu, Yiu-ming Cheung, Bo Han, Defu Lian
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`	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	A*	`conf`	Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation. ICLR Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong
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	J	`jnl`	Characterizing Submanifold Region for Out-of-Distribution Detection. IEEE Trans. Knowl. Data Eng. Xuhui Li, Zhen Fang, Yonggang Zhang, Ning Ma, Jiajun Bu, Bo Han, Haishuai Wang
2025	A*	`conf`	Characterizing Submanifold Region for Out-of-Distribution Detection: (Extended Abstract). ICDE Xuhui Li, Zhen Fang, Yonggang Zhang, Ning Ma, Jiajun Bu, Bo Han, Haishuai Wang
2025	J	`jnl`	Classifying Long-tailed and Label-noise Data via Disentangling and Unlearning. CoRR Chen Shu, Mengke Li, Yiqun Zhang, Yang Lu, Bo Han, Yiu-ming Cheung, Hanzi Wang
2025	J	`jnl`	Co-Reward: Self-supervised Reinforcement Learning for Large Language Model Reasoning via Contrastive Agreement. CoRR Zizhuo Zhang, Jianing Zhu, Xinmu Ge, Zihua Zhao, Zhanke Zhou, Xuan Li, Xiao Feng, Jiangchao Yao, Bo Han
2025	A*	`conf`	Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning. EMNLP Yunhao Gou, Hansi Yang, Zhili Liu, Kai Chen, Yihan Zeng, Lanqing Hong, Zhenguo Li, Qun Liu, Bo Han, James Kwok, Yu Zhang
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`	Detecting Generated Images by Fitting Natural Image Distributions. CoRR Yonggang Zhang, Jun Nie, Xinmei Tian, Mingming Gong, Kun Zhang, Bo Han
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`	EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget. CoRR Liang Chen, Xueting Han, Qizhou Wang, Bo Han, Jing Bai, Hinrich Schutze, Kam-Fai Wong
2025	A*	`conf`	Eliciting Causal Abilities in Large Language Models for Reasoning Tasks. AAAI Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen, Bo Han
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	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	A*	`conf`	Fast and Accurate Blind Flexible Docking. ICLR Zizhuo Zhang, Lijun Wu, Kaiyuan Gao, Jiangchao Yao, Tao Qin, Bo Han
2025	J	`jnl`	Fast and Accurate Blind Flexible Docking. CoRR Zizhuo Zhang, Lijun Wu, Kaiyuan Gao, Jiangchao Yao, Tao Qin, Bo Han
2025	J	`jnl`	FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning. CoRR Zhiqin Yang, Yonggang Zhang, Chenxin Li, Yiu-ming Cheung, Bo Han, Yixuan Yuan
2025	J	`jnl`	Federated Generalized Novel Category Discovery with Prompts Tuning. Trans. Mach. Learn. Res. Lei Shen, Nan Pu, Zhun Zhong, Mingming Gong, Dianhai Yu, Chengqi Zhang, Bo Han
2025	J	`jnl`	Federated Noisy Client Learning. IEEE Trans. Neural Networks Learn. Syst. Kahou Tam, Li Li, Bo Han, Cheng-Zhong Xu, Huazhu Fu
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`	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	A*	`conf`	From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? ICML Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han
2025	J	`jnl`	From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? CoRR Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han
2025	A*	`conf`	GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs. ICML Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han
2025	J	`jnl`	GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models. CoRR Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han
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	A*	`conf`	Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection. ICLR Lei Shen, Zhenheng Tang, Lijun Wu, Yonggang Zhang, Xiaowen Chu, Tao Qin, Bo Han
2025	J	`jnl`	Image-based Multimodal Models as Intruders: Transferable Multimodal Attacks on Video-based MLLMs. CoRR Linhao Huang, Xue Jiang, Zhiqiang Wang, Wentao Mo, Xi Xiao, Bo Han, Yongjie Yin, Feng Zheng
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	J	`jnl`	InsGNN: Interpretable spatio-temporal graph neural networks via information bottleneck. Inf. Fusion Hui Fang, Haishuai Wang, Yang Gao, Yonggang Zhang, Jiajun Bu, Bo Han, Hui Lin
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`	Knowledge-Enhanced Facial Expression Recognition With Emotional-to-Neutral Transformation. IEEE Trans. Multim. Hangyu Li, Yihan Xu, Jiangchao Yao, Nannan Wang, Xinbo Gao, Bo Han
2025	J	`jnl`	LLM Unlearning with LLM Beliefs. CoRR Kemou Li, Qizhou Wang, Yue Wang, Fengpeng Li, Jun Liu, Bo Han, Jiantao Zhou
2025	J	`jnl`	Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models. CoRR Zhanke Zhou, Zhaocheng Zhu, Xuan Li, Mikhail Galkin, Xiao Feng, Sanmi Koyejo, Jian Tang, Bo Han
2025	J	`jnl`	Lang-PINN: From Language to Physics-Informed Neural Networks via a Multi-Agent Framework. CoRR Xin He, Liangliang You, Hongduan Tian, Bo Han, Ivor W. Tsang, Yew-Soon Ong
2025	J	`jnl`	Learning to Instruct for Visual Instruction Tuning. CoRR Zhihan Zhou, Feng Hong, Jiaan Luo, Jiangchao Yao, Dongsheng Li, Bo Han, Ya Zhang, Yanfeng Wang
2025	A*	`conf`	Learning without Isolation: Pathway Protection for Continual Learning. ICML Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren
2025	J	`jnl`	Learning without Isolation: Pathway Protection for Continual Learning. CoRR Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li, Jingfeng Zhang, Bo Han, Gang Niu, Houfang Liu, Yi Yang, Sifan Yang, Changshui Zhang, Tianling Ren
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`	On the Thinking-Language Modeling Gap in Large Language Models. CoRR Chenxi Liu, Yongqiang Chen, Tongliang Liu, James Cheng, Bo Han, Kun Zhang
2025	A*	`conf`	One-shot Federated Learning Methods: A Practical Guide. IJCAI Xiang Liu, Zhenheng Tang, Xia Li, Yijun Song, Sijie Ji, Zemin Liu, Bo Han, Linshan Jiang, Jialin Li
2025	J	`jnl`	One-shot Federated Learning Methods: A Practical Guide. CoRR Xiang Liu, Zhenheng Tang, Xia Li, Yijun Song, Sijie Ji, Zemin Liu, Bo Han, Linshan Jiang, Jialin Li
2025	B	`conf`	Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models. COLING Xinyu Pang, Ruixin Hong, Zhanke Zhou, Fangrui Lv, Xinwei Yang, Zhilong Liang, Bo Han, Changshui Zhang
2025	J	`jnl`	Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection. CoRR Shuhai Zhang, Zihao Lian, Jiahao Yang, Daiyuan Li, Guoxuan Pang, Feng Liu, Bo Han, Shutao Li, Mingkui Tan
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`	RML++: Regroup Median Loss for Combating Label Noise. Int. J. Comput. Vis. Fengpeng Li, Kemou Li, Qizhou Wang, Bo Han, Jinyu Tian, Jiantao Zhou
2025	A*	`conf`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. ICLR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	J	`jnl`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. CoRR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	J	`jnl`	Robust Learning under Hybrid Noise. ACM Trans. Intell. Syst. Technol. Yang Wei, Shuo Chen, Shanshan Ye, Bo Han, Chen Gong
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	A*	`conf`	Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition. IJCAI Hangyu Li, Yixin Zhang, Jiangchao Yao, Nannan Wang, Bo Han
2025	J	`jnl`	Towards Scalable Oversight with Collaborative Multi-Agent Debate in Error Detection. CoRR Yongqiang Chen, Gang Niu, James Cheng, Bo Han, Masashi Sugiyama
2025	J	`jnl`	Towards Understanding Valuable Preference Data for Large Language Model Alignment. CoRR Zizhuo Zhang, Qizhou Wang, Shanshan Ye, Jianing Zhu, Jiangchao Yao, Bo Han, Masashi Sugiyama
2025	—	`conf`	Trustworthy AI under Imperfect Web Data. WWW (Companion Volume) Jiangchao Yao, Feng Liu, Bo Han
2025	J	`jnl`	Trustworthy Machine Learning in the Era of Foundation Models. IEEE Intell. Syst. Bo Han
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	J	`jnl`	Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation. CoRR Deyu Zou, Yongqiang Chen, Mufei Li, Siqi Miao, Chenxi Liu, Bo Han, James Cheng, Pan Li
2025	J	`jnl`	What Is Preference Optimization Doing, How and Why? CoRR Yue Wang, Qizhou Wang, Zizhuo Zhang, Ang Li, Gang Niu, Bo Han, Masashi Sugiyama
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	A*	`conf`	A Sober Look at the Robustness of CLIPs to Spurious Features. NeurIPS Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
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	A*	`conf`	Accurate Forgetting for Heterogeneous Federated Continual Learning. ICLR Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama
2024	J	`jnl`	Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds. CoRR Shuhai Zhang, Jiahao Yang, Hui Luo, Jie Chen, Li Wang, Feng Liu, Bo Han, Mingkui Tan
2024	J	`jnl`	Atomas: Hierarchical Alignment on Molecule-Text for Unified Molecule Understanding and Generation. CoRR Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong
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	A*	`conf`	Balancing Similarity and Complementarity for Federated Learning. ICML Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi, Jingfeng Zhang, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
2024	J	`jnl`	Balancing Similarity and Complementarity for Federated Learning. CoRR Kunda Yan, Sen Cui, Abudukelimu Wuerkaixi, Jingfeng Zhang, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
2024	A*	`conf`	Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? NeurIPS Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han
2024	J	`jnl`	Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? CoRR Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han
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`	Decoupling the Class Label and the Target Concept in Machine Unlearning. CoRR Jianing Zhu, Bo Han, Jiangchao Yao, Jianliang Xu, Gang Niu, Masashi Sugiyama
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`	Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy. ICLR Shuhai Zhang, Yiliao Song, Jiahao Yang, Yuanqing Li, Bo Han, Mingkui Tan
2024	J	`jnl`	Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy. CoRR Shuhai Zhang, Yiliao Song, Jiahao Yang, Yuanqing Li, Bo Han, Mingkui Tan
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	J	`jnl`	Do CLIPs Always Generalize Better than ImageNet Models? CoRR Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
2024	J	`jnl`	Does Confusion Really Hurt Novel Class Discovery? Int. J. Comput. Vis. Haoang Chi, Wenjing Yang, Feng Liu, Long Lan, Tao Qin, Bo Han
2024	J	`jnl`	Efficient private SCO for heavy-tailed data via averaged clipping. Mach. Learn. Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Tieyong Zeng
2024	J	`jnl`	Eliciting Causal Abilities in Large Language Models for Reasoning Tasks. CoRR Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen, Bo Han
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 Evolving Domain Generalization through Dynamic Latent Representations. AAAI Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
2024	J	`jnl`	Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
2024	A*	`conf`	Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
2024	J	`jnl`	Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
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	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`	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	J	`jnl`	Exploiting counter-examples for active learning with partial labels. Mach. Learn. Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han
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	J	`jnl`	Federated Learning with Bilateral Curation for Partially Class-Disjoint Data. CoRR Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
2024	A*	`conf`	Federated Learning with Extremely Noisy Clients via Negative Distillation. AAAI Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang
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	A*	`conf`	FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. NeurIPS Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu
2024	J	`jnl`	FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. CoRR Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou, Bo Han, Xiaowen Chu
2024	J	`jnl`	HiFE: Hierarchical Feature Ensemble Framework for Few-shot Hypotheses Adaptation. Trans. Mach. Learn. Res. Yongfeng Zhong, Haoang Chi, Feng Liu, Xiao-Ming Wu, Bo Han
2024	A*	`conf`	How Interpretable Are Interpretable Graph Neural Networks? ICML Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
2024	J	`jnl`	How Interpretable Are Interpretable Graph Neural Networks? CoRR Yongqiang Chen, Yatao Bian, Bo Han, James Cheng
2024	J	`jnl`	Knowledge-Enhanced Facial Expression Recognition with Emotional-to-Neutral Transformation. CoRR Hangyu Li, Yihan Xu, Jiangchao Yao, Nannan Wang, Xinbo Gao, Bo Han
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 a robust foundation model against clean-label data poisoning attacks at downstream tasks. Neural Networks Ting Zhou, Hanshu Yan, Bo Han, Lei Liu, Jingfeng Zhang
2024	A*	`conf`	Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. ICLR Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han
2024	J	`jnl`	Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. CoRR Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han
2024	A*	`conf`	MCM: Multi-condition Motion Synthesis Framework. IJCAI Zeyu Ling, Bo Han, Yongkang Wong, Han Lin, Mohan S. Kankanhalli, Weidong Geng
2024	J	`jnl`	MCM: Multi-condition Motion Synthesis Framework. CoRR Zeyu Ling, Bo Han, Yongkang Wang, Han Lin, Mohan S. Kankanhalli, Weidong Geng
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`	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	A*	`conf`	Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning. CVPR Zihua Zhao, Mengxi Chen, Tianjie Dai, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
2024	J	`jnl`	Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning. CoRR Zihua Zhao, Mengxi Chen, Tianjie Dai, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
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	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 Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel. ICLR Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
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	J	`jnl`	On the Learnability of Out-of-distribution Detection. CoRR Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu
2024	J	`jnl`	On the Learnability of Out-of-distribution Detection. J. Mach. Learn. Res. Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu
2024	A*	`conf`	On the Over-Memorization During Natural, Robust and Catastrophic Overfitting. ICLR Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu
2024	J	`jnl`	Online binary classification from similar and dissimilar data. Mach. Learn. Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng
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`	Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models. CoRR Xinyu Pang, Ruixin Hong, Zhanke Zhou, Fangrui Lv, Xinwei Yang, Zhilong Liang, Bo Han, Changshui Zhang
2024	A*	`conf`	Pseudo-Private Data Guided Model Inversion Attacks. NeurIPS Xiong Peng, Bo Han, Feng Liu, Tongliang Liu, Mingyuan Zhou
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`	Rethinking Improved Privacy-Utility Trade-off with Pre-existing Knowledge for DP Training. CoRR Yu Zheng, Wenchao Zhang, Yonggang Zhang, Wei Song, Kai Zhou, Bo Han
2024	A*	`conf`	Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation. NeurIPS Jiaan Luo, Feng Hong, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
2024	J	`jnl`	Robust Learning under Hybrid Noise. CoRR Yang Wei, Shuo Chen, Shanshan Ye, Bo Han, Chen Gong
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`	Searching to Exploit Memorization Effect in Deep Learning With Noisy Labels. IEEE Trans. Pattern Anal. Mach. Intell. Hansi Yang, Quanming Yao, Bo Han, James T. Kwok
2024	A*	`conf`	Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection. NeurIPS Geng Yu, Jianing Zhu, Jiangchao Yao, Bo Han
2024	J	`jnl`	Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection. CoRR Geng Yu, Jianing Zhu, Jiangchao Yao, Bo Han
2024	J	`jnl`	Server-Client Collaborative Distillation for Federated Reinforcement Learning. ACM Trans. Knowl. Discov. Data Weiming Mai, Jiangchao Yao, Chen Gong, Ya Zhang, Yiu-ming Cheung, Bo Han
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`	Towards Realistic Model Selection for Semi-supervised Learning. ICML Muyang Li, Xiaobo Xia, Runze Wu, Fengming Huang, Jun Yu, Bo Han, Tongliang Liu
2024	A*	`conf`	Trustworthy Machine Learning under Imperfect Data. IJCAI Bo Han
2024	J	`jnl`	USN: A Robust Imitation Learning Method against Diverse Action Noise. J. Artif. Intell. Res. Xingrui Yu, Bo Han, Ivor W. Tsang
2024	J	`jnl`	Understanding Fairness Surrogate Functions in Algorithmic Fairness. Trans. Mach. Learn. Res. Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong 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	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
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`	AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. KDD Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
2023	A*	`conf`	Adjustment and Alignment for Unbiased Open Set Domain Adaptation. CVPR Wuyang Li, Jie Liu, Bo Han, Yixuan Yuan
2023	J	`jnl`	Are All Unseen Data Out-of-Distribution? CoRR Songming Zhang, Yuxiao Luo, Qizhou Wang, Haoang Chi, Weikai Li, Bo Han, Jinyan Li
2023	J	`jnl`	Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks. CoRR Jingfeng Zhang, Bo Song, Bo Han, Lei Liu, Gang Niu, Masashi Sugiyama
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	J	`jnl`	Class-Wise Denoising for Robust Learning Under Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. Chen Gong, Yongliang Ding, Bo Han, Gang Niu, Jian Yang, Jane You, Dacheng Tao, Masashi Sugiyama
2023	A*	`conf`	Combating Bilateral Edge Noise for Robust Link Prediction. NeurIPS Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han
2023	J	`jnl`	Combating Bilateral Edge Noise for Robust Link Prediction. CoRR Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han
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`	Combating Representation Learning Disparity with Geometric Harmonization. NeurIPS Zhihan Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Bo Han, Yanfeng Wang
2023	J	`jnl`	Combating Representation Learning Disparity with Geometric Harmonization. CoRR Zhihan Zhou, Jiangchao Yao, Feng Hong, Ya Zhang, Bo Han, Yanfeng Wang
2023	J	`jnl`	Deep Learning From Multiple Noisy Annotators as A Union. IEEE Trans. Neural Networks Learn. Syst. Hongxin Wei, Renchunzi Xie, Lei Feng, Bo Han, Bo An
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	A*	`conf`	Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score. ICML Shuhai Zhang, Feng Liu, Jiahao Yang, Yifan Yang, Changsheng Li, Bo Han, Mingkui Tan
2023	J	`jnl`	Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score. CoRR Shuhai Zhang, Feng Liu, Jiahao Yang, Yifan Yang, Changsheng Li, Bo Han, Mingkui Tan
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	A*	`conf`	Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
2023	J	`jnl`	Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
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	J	`jnl`	Exploiting Counter-Examples for Active Learning with Partial labels. CoRR Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, 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	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`	Federated Learning with Bilateral Curation for Partially Class-Disjoint Data. NeurIPS Ziqing Fan, Ruipeng Zhang, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
2023	J	`jnl`	Federated Learning with Extremely Noisy Clients via Negative Distillation. CoRR Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang
2023	J	`jnl`	Federated Semi-Supervised Learning with Annotation Heterogeneity. CoRR Xinyi Shang, Gang Huang, Yang Lu, Jian Lou, Bo Han, Yiu-ming Cheung, Hanzi Wang
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`	GRACE: A General Graph Convolution Framework for Attributed Graph Clustering. ACM Trans. Knowl. Discov. Data Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
2023	A*	`conf`	Hard Sample Matters a Lot in Zero-Shot Quantization. CVPR Huantong Li, Xiangmiao Wu, Fanbing Lv, Daihai Liao, Thomas H. Li, Yonggang Zhang, Bo Han, Mingkui Tan
2023	J	`jnl`	Hard Sample Matters a Lot in Zero-Shot Quantization. CoRR Huantong Li, Xiangmiao Wu, Fanbing Lv, Daihai Liao, Thomas H. Li, Yonggang Zhang, Bo Han, Mingkui Tan
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	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`	Label-Noise Learning with Intrinsically Long-Tailed Data. ICCV Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung, Hanzi Wang
2023	J	`jnl`	Latent Class-Conditional Noise Model. CoRR Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang
2023	J	`jnl`	Latent Class-Conditional Noise Model. IEEE Trans. Pattern Anal. Mach. Intell. Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang
2023	J	`jnl`	Learning to Augment Distributions for Out-of-Distribution Detection. CoRR Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023	A*	`conf`	Learning to Augment Distributions for Out-of-distribution Detection. NeurIPS Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023	J	`jnl`	Long-Range Neural Atom Learning for Molecular Graphs. CoRR Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
2023	J	`jnl`	MCM: Multi-condition Motion Synthesis Framework for Multi-scenario. CoRR Zeyu Ling, Bo Han, Yongkang Wong, Mohan S. Kankanhalli, Weidong Geng
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	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`	Moderately Distributional Exploration for Domain Generalization. ICML Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian
2023	J	`jnl`	Moderately Distributional Exploration for Domain Generalization. CoRR Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian
2023	A*	`conf`	NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension. AAAI Xin He, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung, Simon See, Bo Han, Xiaowen Chu
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	A*	`conf`	On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. ICML Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han
2023	J	`jnl`	On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. CoRR Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han
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	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`	Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
2023	A*	`conf`	Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis. ICCV Ke Liu, Feng Liu, Haishuai Wang, Ning Ma, Jiajun Bu, Bo Han
2023	J	`jnl`	Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis. CoRR Ke Liu, Feng Liu, Haishuai Wang, Ning Ma, Jiajun Bu, Bo Han
2023	J	`jnl`	Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng
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	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	A*	`conf`	SODA: Robust Training of Test-Time Data Adaptors. NeurIPS Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han
2023	J	`jnl`	SODA: Robust Training of Test-Time Data Adaptors. CoRR Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han
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	J	`jnl`	Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
2023	J	`jnl`	Towards out-of-distribution generalizable predictions of chemical kinetics properties. CoRR Zihao Wang, Yongqiang Chen, Yang Duan, Weijiang Li, Bo Han, James Cheng, Hanghang Tong
2023	J	`jnl`	Understanding Fairness Surrogate Functions in Algorithmic Fairness. CoRR Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong Liu
2023	A*	`conf`	Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
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`	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	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	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	J	`jnl`	Combating Noisy-Labeled and Imbalanced Data by Two Stage Bi-Dimensional Sample Selection. CoRR Yiliang Zhang, Yang Lu, Bo Han, Yiu-ming Cheung, Hanzi Wang
2022	A*	`conf`	Contrastive Learning with Boosted Memorization. ICML Zhihan Zhou, Jiangchao Yao, Yanfeng Wang, Bo Han, Ya Zhang
2022	J	`jnl`	Contrastive Learning with Boosted Memorization. CoRR Zhihan Zhou, Jiangchao Yao, Yanfeng Wang, Bo Han, Ya Zhang
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`	Device-Cloud Collaborative Recommendation via Meta Controller. CoRR Jiangchao Yao, Feng Wang, Xichen Ding, Shaohu Chen, Bo Han, Jingren Zhou, Hongxia Yang
2022	A*	`conf`	Device-cloud Collaborative Recommendation via Meta Controller. KDD Jiangchao Yao, Feng Wang, Xichen Ding, Shaohu Chen, Bo Han, Jingren Zhou, Hongxia Yang
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	—	`conf`	EAGAN: Efficient Two-Stage Evolutionary Architecture Search for GANs. ECCV (16) Guohao Ying, Xin He, Bin Gao, Bo Han, Xiaowen Chu
2022	J	`jnl`	Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang
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`	Exact Shape Correspondence via 2D graph convolution. NeurIPS Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng
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	—	`conf`	Fair Classification with Instance-dependent Label Noise. CLeaR Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu
2022	A*	`conf`	Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. ICML Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
2022	J	`jnl`	Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. CoRR Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
2022	J	`jnl`	FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels. CoRR Zhuowei Wang, Tianyi Zhou, Guodong Long, Bo Han, Jing Jiang
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	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	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`	Is Out-of-Distribution Detection Learnable? NeurIPS Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu
2022	J	`jnl`	Is Out-of-Distribution Detection Learnable? CoRR Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu
2022	J	`jnl`	Learning Adaptive Propagation for Knowledge Graph Reasoning. CoRR Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
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	J	`jnl`	Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization. CoRR Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok
2022	J	`jnl`	Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization. J. Mach. Learn. Res. Quanming Yao, Yaqing Wang, Bo Han, James T. Kwok
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 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`	Modeling Adversarial Noise for Adversarial Training. ICML Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu
2022	J	`jnl`	NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension. CoRR Xin He, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung, Simon See, Bo Han, Xiaowen Chu
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	J	`jnl`	Pareto Invariant Risk Minimization. CoRR Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
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	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	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	J	`jnl`	SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. Trans. Mach. Learn. Res. Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long
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	A*	`conf`	Synergy-of-Experts: Collaborate to Improve Adversarial Robustness. NeurIPS Sen Cui, Jingfeng Zhang, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang
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	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	A*	`conf`	Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. ICML Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu
2022	J	`jnl`	Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning. CoRR Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xin He, Bo Han, Xiaowen Chu
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	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	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	J	`jnl`	Click-through Rate Prediction with Auto-Quantized Contrastive Learning. CoRR Yujie Pan, Jiangchao Yao, Bo Han, Kunyang Jia, Ya Zhang, Hongxia Yang
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`	Device-Cloud Collaborative Learning for Recommendation. KDD Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Jingren Zhou, Hongxia Yang
2021	J	`jnl`	Device-Cloud Collaborative Learning for Recommendation. CoRR Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Jingren Zhou, Hongxia Yang
2021	J	`jnl`	EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs. CoRR Guohao Ying, Xin He, Bin Gao, Bo Han, Xiaowen Chu
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`	Federated Noisy Client Learning. CoRR Li Li, Huazhu Fu, Bo Han, Cheng-Zhong Xu, Ling Shao
2021	A	`conf`	Fraud Detection under Multi-Sourced Extremely Noisy Annotations. CIKM Chuang Zhang, Qizhou Wang, Tengfei Liu, Xun Lu, Jin Hong, Bo Han, Chen Gong
2021	A*	`conf`	Geometry-aware Instance-reweighted Adversarial Training. ICLR Jingfeng Zhang, Jianing Zhu, Gang Niu, Bo Han, Masashi Sugiyama, Mohan S. Kankanhalli
2021	A	`conf`	HyperGraph Convolution Based Attributed HyperGraph Clustering. CIKM Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
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`	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	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`	Local Reweighting for Adversarial Training. CoRR Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng
2021	J	`jnl`	MC$^2$-SF: Slow-Fast Learning for Mobile-Cloud Collaborative Recommendation. CoRR Zeyuan Chen, Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Wei Zhang, Hongxia Yang
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	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`	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`	Pointwise Binary Classification with Pairwise Confidence Comparisons. ICML Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2021	J	`jnl`	Privacy-Preserving Stochastic Gradual Learning. IEEE Trans. Knowl. Data Eng. Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu
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	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`	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	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	A*	`conf`	Universal Semi-Supervised Learning. NeurIPS Zhuo Huang, Chao Xue, Bo Han, Jian Yang, Chen Gong
2020	A*	`conf`	A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery. IJCAI Yijing Luo, Bo Han, Chen Gong
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	A*	`conf`	Attacks Which Do Not Kill Training Make Adversarial Learning Stronger. ICML Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli
2020	J	`jnl`	Attacks Which Do Not Kill Training Make Adversarial Learning Stronger. CoRR Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli
2020	A*	`conf`	Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling. AAAI Chao Li, Mohammad Emtiyaz Khan, Zhun Sun, Gang Niu, Bo Han, Shengli Xie, Qibin Zhao
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	—	`conf`	Confusable Learning for Large-Class Few-Shot Classification. ECML/PKDD (2) Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long
2020	J	`jnl`	Confusable Learning for Large-class Few-Shot Classification. CoRR Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long
2020	A*	`conf`	Cross-Graph: Robust and Unsupervised Embedding for Attributed Graphs with Corrupted Structure. ICDM Chun Wang, Bo Han, Shirui Pan, Jing Jiang, Gang Niu, Guodong Long
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	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	J	`jnl`	Geometry-aware Instance-reweighted Adversarial Training. CoRR Jingfeng Zhang, Jianing Zhu, Gang Niu, Bo Han, Masashi Sugiyama, Mohan S. Kankanhalli
2020	A*	`conf`	Learning with Multiple Complementary Labels. ICML Lei Feng, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama
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	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`	Pointwise Binary Classification with Pairwise Confidence Comparisons. CoRR Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
2020	A*	`conf`	Provably Consistent Partial-Label Learning. NeurIPS Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama
2020	J	`jnl`	Provably Consistent Partial-Label Learning. CoRR Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama
2020	A*	`conf`	SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama
2020	A*	`conf`	Searching to Exploit Memorization Effect in Learning with Noisy Labels. ICML Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok
2020	J	`jnl`	SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. CoRR Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long
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	A*	`conf`	Variational Imitation Learning with Diverse-quality Demonstrations. ICML Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama
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`	Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. Bo Han, Ivor W. Tsang, Ling Chen, Joey Tianyi Zhou, Celina Ping Yu
2019	J	`jnl`	Butterfly: A Panacea for All Difficulties in Wildly Unsupervised Domain Adaptation. CoRR Feng Liu, Jie Lu, Bo Han, Gang Niu, Guangquan Zhang, Masashi Sugiyama
2019	A*	`conf`	Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations. ICML Quanming Yao, James Tin-Yau Kwok, Bo Han
2019	A*	`conf`	How does Disagreement Help Generalization against Label Corruption? ICML Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama
2019	J	`jnl`	How does Disagreement Help Generalization against Label Corruption? CoRR Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama
2019	J	`jnl`	Millionaire: a hint-guided approach for crowdsourcing. Mach. Learn. Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama
2019	J	`jnl`	Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative. CoRR Miao Xu, Bingcong Li, Gang Niu, Bo Han, Masashi Sugiyama
2019	J	`jnl`	Searching to Exploit Memorization Effect in Learning from Corrupted Labels. CoRR Hansi Yang, Quanming Yao, Bo Han, Gang Niu
2019	J	`jnl`	Towards Robust ResNet: A Small Step but A Giant Leap. CoRR Jingfeng Zhang, Bo Han, Laura Wynter, Kian Hsiang Low, Mohan S. Kankanhalli
2019	A*	`conf`	Towards Robust ResNet: A Small Step but a Giant Leap. IJCAI Jingfeng Zhang, Bo Han, Laura Wynter, Bryan Kian Hsiang Low, Mohan S. Kankanhalli
2019	J	`jnl`	VILD: Variational Imitation Learning with Diverse-quality Demonstrations. CoRR Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama
2019	—	`conf`	VisDrone-SOT2019: The Vision Meets Drone Single Object Tracking Challenge Results. ICCV Workshops Dawei Du, Yue Zhang, Liefeng Bo, Hailin Shi, Rui Zhu, Bo Han, Chunhui Zhang, Guizhong Liu, Han Wu, Hao Wen, Haoran Wang, Pengfei Zhu, Jiaqing Fan, Jie Chen, Jie Gao, Jie Zhang, Jinghao Zhou, Jinliu Zhou, Jinwang Wang, Jiuqing Wan, Josef Kittler, Kaihua Zhang, Longyin Wen, Kaiqi Huang, Kang Yang, Kangkai Zhang, Lianghua Huang, Lijun Zhou, Lingling Shi, Lu Ding, Ning Wang, Peng Wang, Qintao Hu, Xiao Bian, Robert Laganière, Ruiyan Ma, Ruohan Zhang, Shanrong Zou, Shengwei Zhao, Shengyang Li, Shengyin Zhu, Shikun Li, Shiming Ge, Shiyu Xuan, Haibin Ling, Tianyang Xu, Ting He, Wei Shi, Wei Song, Weiming Hu, Wenhua Zhang, Wenjun Zhu, Xi Yu, Xianhai Wang, Xiaojun Wu, Qinghua Hu, Xiaotong Li, Xiaoxue Li, Xiaoyue Yin, Xin Zhang, Xin Zhao, Xizhe Xue, Xu Lei, Xueyuan Yang, Yanjie Gao, Yanyun Zhao, Jiayu Zheng, Yinda Xu, Ying Li, Yong Wang, Yong Yang, Yuting Yang, Yuxuan Li, Zeyu Wang, Zhenhua Feng, Zhipeng Zhang, Zhiyong Yu, Tao Peng, Zhizhao Duan, Zhuojin Sun, Xinyao Wang
2019	J	`jnl`	Where is the Bottleneck of Adversarial Learning with Unlabeled Data? CoRR Jingfeng Zhang, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
2018	J	`jnl`	Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama
2018	A*	`conf`	Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama
2018	A*	`conf`	Masking: A New Perspective of Noisy Supervision. NeurIPS Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama
2018	J	`jnl`	Masking: A New Perspective of Noisy Supervision. CoRR Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama
2018	J	`jnl`	Matrix Co-completion for Multi-label Classification with Missing Features and Labels. CoRR Miao Xu, Gang Niu, Bo Han, Ivor W. Tsang, Zhi-Hua Zhou, Masashi Sugiyama
2018	J	`jnl`	Millionaire: A Hint-guided Approach for Crowdsourcing. CoRR Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama
2018	J	`jnl`	Privacy-preserving Stochastic Gradual Learning. CoRR Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu
2018	J	`jnl`	Progressive Stochastic Learning for Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. Bo Han, Ivor W. Tsang, Ling Chen, Celina Ping Yu, Sai-Fu Fung
2018	J	`jnl`	Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. CoRR Bo Han, Gang Niu, Jiangchao Yao, Xingrui Yu, Miao Xu, Ivor W. Tsang, Masashi Sugiyama
2018	J	`jnl`	Robust Plackett-Luce model for k-ary crowdsourced preferences. Mach. Learn. Bo Han, Yuangang Pan, Ivor W. Tsang
2018	J	`jnl`	Stagewise learning for noisy k-ary preferences. Mach. Learn. Yuangang Pan, Bo Han, Ivor W. Tsang
2016	J	`jnl`	On the Convergence of A Family of Robust Losses for Stochastic Gradient Descent. CoRR Bo Han, Ivor W. Tsang, Ling Chen
2016	—	`conf`	On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. ECML/PKDD (1) Bo Han, Ivor W. Tsang, Ling Chen