James T. Kwok

301 papers A* 89A 6B 13C 4Misc 1Journal 145Unranked 33
YearRankTypeTitle / Venue / Authors
2026 J jnl
Alignment of Diffusion Models: Fundamentals, Challenges, and Future.
ACM Comput. Surv.
Buhua Liu, Shitong Shao, Bao Li, Lichen Bai, Zhiqiang Xu, Haoyi Xiong, James T. Kwok, Sumi Helal, Zeke Xie
2026 J jnl
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation.
ACM Comput. Surv.
Xiaofeng Cao, Mingwei Xu, Xin Yu, Jiangchao Yao, Wei Ye, Sheng-Jun Huang, Min-Ling Zhang, Ivor W. Tsang, Yew-Soon Ong, James T. Kwok, Heng Tao Shen
2026 J jnl
Beyond the Grid: Layout-Informed Multi-Vector Retrieval with Parsed Visual Document Representations.
CoRR
Yibo Yan, Mingdong Ou, Yi Cao, Xin Zou, Shuliang Liu, Jiahao Huo, Yue Huang, James T. Kwok, Xuming Hu
2026 J jnl
CompleMatch: Boosting Time-Series Semi-Supervised Classification With Temporal-Frequency Complementarity.
IEEE Trans. Pattern Anal. Mach. Intell.
Zhen Liu, Kun Zeng, Qianli Ma, James T. Kwok
2026 J jnl
Dual-balancing for multi-task learning.
Neural Networks
Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, Ivor W. Tsang, James T. Kwok
2026 J jnl
DynamicGTR: Leveraging Graph Topology Representation Preferences to Boost VLM Capabilities on Graph QAs.
CoRR
Yanbin Wei, Jiangyue Yan, Chun Kang, Yang Chen, Hua Liu, James T. Kwok, Yu Zhang
2026 J jnl
Mixture of Cluster-Conditional LoRA Experts for Vision-Language Instruction Tuning.
IEEE Trans. Image Process.
Yunhao Gou, Zhili Liu, Kai Chen, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok, Yu Zhang
2025 J jnl
Alternating Training-based Label Smoothing Enhances Prompt Generalization.
CoRR
Yang Chen, Yanbin Wei, Ke Jin, Yi Kong, James T. Kwok, Yu Zhang
2025 J jnl
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation.
CoRR
Xiaofeng Cao, Mingwei Xu, Xin Yu, Jiangchao Yao, Wei Ye, Shengjun Huang, Minling Zhang, Ivor W. Tsang, Yew Soon Ong, James T. Kwok, Heng Tao Shen
2025 J jnl
Bubble, Bubble, AI's Rumble: Why Global Financial Regulatory Incident Reporting is Our Shield Against Systemic Stumbles.
CoRR
Anchal Gupta, Gleb Pappyshev, James T. Kwok
2025 J jnl
Corrupted but Not Broken: Rethinking the Impact of Corrupted Data in Visual Instruction Tuning.
CoRR
Yunhao Gou, Hansi Yang, Zhili Liu, Kai Chen, Yihan Zeng, Lanqing Hong, Zhenguo Li, Qun Liu, James T. Kwok, Yu Zhang
2025 J jnl
Domain-guided conditional diffusion model for unsupervised domain adaptation.
Neural Networks
Yulong Zhang, Shuhao Chen, Weisen Jiang, Yu Zhang, Jiangang Lu, James T. Kwok
2025 J jnl
DynamicMind: A Tri-Mode Thinking System for Large Language Models.
CoRR
Wei Li, Yanbin Wei, Qiushi Huang, Jiangyue Yan, Yang Chen, James T. Kwok, Yu Zhang
2025 A* conf
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions.
CVPR
Kai Chen, Yunhao Gou, Runhui Huang, Zhili Liu, Daxin Tan, Jing Xu, Chunwei Wang, Yi Zhu, Yihan Zeng, Kuo Yang, Dingdong Wang, Kun Xiang, Haoyuan Li, Haoli Bai, Jianhua Han, Xiaohui Li, Weike Jin, Nian Xie, Yu Zhang, James T. Kwok, Hengshuang Zhao, Xiaodan Liang, Dit-Yan Yeung, Xiao Chen, Zhenguo Li, Wei Zhang, Qun Liu, Lanqing Hong, Lu Hou, Hang Xu
2025 — conf
End-to-End Optimization for Multimodal Retrieval-Augmented Generation via Reward Backpropagation.
EMNLP (Findings)
Zhiyuan Fan, Longfei Yun, Ming Yan, Yumeng Wang, Dadi Guo, Brian Mak, James T. Kwok, Yi R. Fung
2025 J jnl
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond.
CoRR
Weiyu Chen, Xiaoyuan Zhang, Baijiong Lin, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok
2025 J jnl
Harnessing Adaptive Topology Representations for Zero-Shot Graph Question Answering.
CoRR
Yanbin Wei, Jiangyue Yan, Chun Kang, Yang Chen, Hua Liu, James T. Kwok, Yu Zhang
2025 A* conf
Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization.
ICLR
Hansi Yang, James T. Kwok
2025 — conf
Mixture of insighTful Experts (MoTE): The Synergy of Reasoning Chains and Expert Mixtures in Self-Alignment.
ACL (1)
Zhili Liu, Yunhao Gou, Kai Chen, Lanqing Hong, Jiahui Gao, Fei Mi, Yu Zhang, Zhenguo Li, Xin Jiang, Qun Liu, James T. Kwok
2025 J jnl
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting.
CoRR
Ziyu Zhou, Jiaxi Hu, Qingsong Wen, James T. Kwok, Yuxuan Liang
2025 A* conf
Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction.
ICML
Yanbin Wei, Xuehao Wang, Zhan Zhuang, Yang Chen, Shuhao Chen, Yulong Zhang, James T. Kwok, Yu Zhang
2025 J jnl
Open the Eyes of MPNN: Vision Enhances MPNN in Link Prediction.
CoRR
Yanbin Wei, Xuehao Wang, Zhan Zhuang, Yang Chen, Shuhao Chen, Yulong Zhang, Yu Zhang, James T. Kwok
2025 A* conf
Pareto Merging: Multi-Objective Optimization for Preference-Aware Model Merging.
ICML
Weiyu Chen, James T. Kwok
2025 J jnl
Perceptual Decoupling for Scalable Multi-modal Reasoning via Reward-Optimized Captioning.
CoRR
Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Xin Jin, Zhenguo Li, James T. Kwok, Yu Zhang
2025 J jnl
Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting.
CoRR
Ziyu Zhou, Yiming Huang, Yanyun Wang, Yuankai Wu, James T. Kwok, Yuxuan Liang
2025 J jnl
Sandbox: safeguarded multi-label learning through safe optimal transport.
Mach. Learn.
Lefei Zhang, Geng Yu, Jiangchao Yao, Yew-Soon Ong, Ivor W. Tsang, James T. Kwok
2024 J jnl
A Survey on Time-Series Pre-Trained Models.
IEEE Trans. Knowl. Data Eng.
Qianli Ma, Zhen Liu, Zhenjing Zheng, Ziyang Huang, Siying Zhu, Zhongzhong Yu, James T. Kwok
2024 J jnl
Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning.
CoRR
Hansi Yang, James T. Kwok
2024 J jnl
Direct Alignment of Language Models via Quality-Aware Self-Refinement.
CoRR
Runsheng Yu, Yong Wang, Xiaoqi Jiao, Youzhi Zhang, James T. Kwok
2024 J jnl
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions.
CoRR
Kai Chen, Yunhao Gou, Runhui Huang, Zhili Liu, Daxin Tan, Jing Xu, Chunwei Wang, Yi Zhu, Yihan Zeng, Kuo Yang, Dingdong Wang, Kun Xiang, Haoyuan Li, Haoli Bai, Jianhua Han, Xiaohui Li, Weike Jin, Nian Xie, Yu Zhang, James T. Kwok, Hengshuang Zhao, Xiaodan Liang, Dit-Yan Yeung, Xiao Chen, Zhenguo Li, Wei Zhang, Qun Liu, Jun Yao, Lanqing Hong, Lu Hou, Hang Xu
2024 A* conf
Efficient Pareto Manifold Learning with Low-Rank Structure.
ICML
Weiyu Chen, James T. Kwok
2024 J jnl
Efficient Pareto Manifold Learning with Low-Rank Structure.
CoRR
Weiyu Chen, James T. Kwok
2024 J jnl
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation.
CoRR
Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok, Yu Zhang
2024 — conf
Eyes Closed, Safety on: Protecting Multimodal LLMs via Image-to-Text Transformation.
ECCV (17)
Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok, Yu Zhang
2024 — conf
Forward-Backward Reasoning in Large Language Models for Mathematical Verification.
ACL (Findings)
Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok
2024 A* conf
GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning.
NeurIPS
Yanbin Wei, Shuai Fu, Weisen Jiang, Zejian Zhang, Zhixiong Zeng, Qi Wu, James T. Kwok, Yu Zhang
2024 — conf
Implicit Concept Removal of Diffusion Models.
ECCV (21)
Zhili Liu, Kai Chen, Yifan Zhang, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok
2024 A* conf
Improving Sharpness-Aware Minimization by Lookahead.
ICML
Runsheng Yu, Youzhi Zhang, James T. Kwok
2024 J jnl
KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion.
CoRR
Yanbin Wei, Qiushi Huang, James T. Kwok, Yu Zhang
2024 — conf
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy.
ECCV (65)
Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James T. Kwok
2024 J jnl
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy.
CoRR
Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James T. Kwok
2024 J jnl
Mentored Learning: Improving Generalization and Convergence of Student Learner.
J. Mach. Learn. Res.
Xiaofeng Cao, Yaming Guo, Heng Tao Shen, Ivor W. Tsang, James T. Kwok
2024 A* conf
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.
ICLR
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu
2024 J jnl
Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment.
CoRR
Zhili Liu, Yunhao Gou, Kai Chen, Lanqing Hong, Jiahui Gao, Fei Mi, Yu Zhang, Zhenguo Li, Xin Jiang, Qun Liu, James T. Kwok
2024 J jnl
Mixup Augmentation with Multiple Interpolations.
CoRR
Lifeng Shen, Jincheng Yu, Hansi Yang, James T. Kwok
2024 A* conf
Multi-Resolution Diffusion Models for Time Series Forecasting.
ICLR
Lifeng Shen, Weiyu Chen, James T. Kwok
2024 A* conf
PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.
ICLR
Junsong Chen, Jincheng Yu, Chongjian Ge, Lewei Yao, Enze Xie, Zhongdao Wang, James T. Kwok, Ping Luo, Huchuan Lu, Zhenguo Li
2024 J jnl
Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment.
IEEE Trans. Neural Networks Learn. Syst.
Fan Feng, Lu Hou, Qi She, Rosa H. M. Chan, James T. Kwok
2024 J jnl
Rendering Graphs for Graph Reasoning in Multimodal Large Language Models.
CoRR
Yanbin Wei, Shuai Fu, Weisen Jiang, James T. Kwok, Yu Zhang
2024 A* conf
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models.
NeurIPS
Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang
2024 J jnl
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models.
CoRR
Shuhao Chen, Weisen Jiang, Baijiong Lin, James T. Kwok, Yu Zhang
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 J jnl
Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts.
CoRR
Zhili Liu, Kai Chen, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, James T. Kwok
2024 J jnl
You Only Merge Once: Learning the Pareto Set of Preference-Aware Model Merging.
CoRR
Weiyu Chen, James T. Kwok
2023 J jnl
A Survey on Time-Series Pre-Trained Models.
CoRR
Qianli Ma, Zhen Liu, Zhenjing Zheng, Ziyang Huang, Siying Zhu, Zhongzhong Yu, James T. Kwok
2023 J jnl
Aggregation Weighting of Federated Learning via Generalization Bound Estimation.
CoRR
Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang, James T. Kwok
2023 A* conf
An Adaptive Policy to Employ Sharpness-Aware Minimization.
ICLR
Weisen Jiang, Hansi Yang, Yu Zhang, James T. Kwok
2023 J jnl
An Adaptive Policy to Employ Sharpness-Aware Minimization.
CoRR
Weisen Jiang, Hansi Yang, Yu Zhang, James T. Kwok
2023 J jnl
Bilinear Scoring Function Search for Knowledge Graph Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Yongqi Zhang, Quanming Yao, James T. Kwok
2023 Misc conf
Cross-Modal Matching and Adaptive Graph Attention Network for RGB-D Scene Recognition.
ICASSP
Yuhui Guo, Xun Liang, James T. Kwok, Xiangping Zheng, Bo Wu, Yuefeng Ma
2023 J jnl
Domain-Guided Conditional Diffusion Model for Unsupervised Domain Adaptation.
CoRR
Yulong Zhang, Shuhao Chen, Weisen Jiang, Yu Zhang, Jiangang Lu, James T. Kwok
2023 A* conf
Effective Structured Prompting by Meta-Learning and Representative Verbalizer.
ICML
Weisen Jiang, Yu Zhang, James T. Kwok
2023 J jnl
Effective Structured Prompting by Meta-Learning and Representative Verbalizer.
CoRR
Weisen Jiang, Yu Zhang, James T. Kwok
2023 J jnl
Effective and Parameter-Efficient Reusing Fine-Tuned Models.
CoRR
Weisen Jiang, Baijiong Lin, Han Shi, Yu Zhang, Zhenguo Li, James T. Kwok
2023 A* conf
Efficient Hyper-parameter Optimization with Cubic Regularization.
NeurIPS
Zhenqian Shen, Hansi Yang, Yong Li, James T. Kwok, Quanming Yao
2023 A* conf
Enhancing Meta Learning via Multi-Objective Soft Improvement Functions.
ICLR
Runsheng Yu, Weiyu Chen, Xinrun Wang, James T. Kwok
2023 J jnl
Feedback Pyramid Attention Networks for Single Image Super-Resolution.
IEEE Trans. Circuits Syst. Video Technol.
Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
2023 J jnl
Forward-Backward Reasoning in Large Language Models for Verification.
CoRR
Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok
2023 J jnl
Geom-Erasing: Geometry-Driven Removal of Implicit Concept in Diffusion Models.
CoRR
Zhili Liu, Kai Chen, Yifan Zhang, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok
2023 A* conf
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training.
ICCV
Xinchi Deng, Han Shi, Runhui Huang, Changlin Li, Hang Xu, Jianhua Han, James T. Kwok, Shen Zhao, Wei Zhang, Xiaodan Liang
2023 J jnl
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training.
CoRR
Xinchi Deng, Han Shi, Runhui Huang, Changlin Li, Hang Xu, Jianhua Han, James T. Kwok, Shen Zhao, Wei Zhang, Xiaodan Liang
2023 — conf
KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion.
EMNLP (Findings)
Yanbin Wei, Qiushi Huang, Yu Zhang, James T. Kwok
2023 A* conf
Leveraging per Image-Token Consistency for Vision-Language Pre-training.
CVPR
Yunhao Gou, Tom Ko, Hansi Yang, James T. Kwok, Yu Zhang, Mingxuan Wang
2023 J jnl
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.
CoRR
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu
2023 J jnl
Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning.
CoRR
Yunhao Gou, Zhili Liu, Kai Chen, Lanqing Hong, Hang Xu, Aoxue Li, Dit-Yan Yeung, James T. Kwok, Yu Zhang
2023 A* conf
Non-autoregressive Conditional Diffusion Models for Time Series Prediction.
ICML
Lifeng Shen, James T. Kwok
2023 J jnl
Non-autoregressive Conditional Diffusion Models for Time Series Prediction.
CoRR
Lifeng Shen, James T. Kwok
2023 A* conf
Nonparametric Iterative Machine Teaching.
ICML
Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok
2023 J jnl
Nonparametric Iterative Machine Teaching.
CoRR
Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok
2023 A* conf
Nonparametric Teaching for Multiple Learners.
NeurIPS
Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok
2023 J jnl
Nonparametric Teaching for Multiple Learners.
CoRR
Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok
2023 J jnl
PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.
CoRR
Junsong Chen, Jincheng Yu, Chongjian Ge, Lewei Yao, Enze Xie, Yue Wu, Zhongdao Wang, James T. Kwok, Ping Luo, Huchuan Lu, Zhenguo Li
2023 A conf
Positive-Unlabeled Node Classification with Structure-aware Graph Learning.
CIKM
Hansi Yang, Yongqi Zhang, Quanming Yao, James T. Kwok
2023 J jnl
Positive-Unlabeled Node Classification with Structure-aware Graph Learning.
CoRR
Hansi Yang, Yongqi Zhang, Quanming Yao, James T. Kwok
2023 J jnl
Searching a High Performance Feature Extractor for Text Recognition Network.
IEEE Trans. Pattern Anal. Mach. Intell.
Hui Zhang, Quanming Yao, James T. Kwok, Xiang Bai
2023 A* conf
Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts.
ICLR
Zhili Liu, Kai Chen, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, James T. Kwok
2022 J jnl
Efficient Low-Rank Semidefinite Programming With Robust Loss Functions.
IEEE Trans. Pattern Anal. Mach. Intell.
Quanming Yao, Hansi Yang, En-Liang Hu, James T. Kwok
2022 A* conf
Efficient Variance Reduction for Meta-learning.
ICML
Hansi Yang, James T. Kwok
2022 J jnl
Leveraging per Image-Token Consistency for Vision-Language Pre-training.
CoRR
Yunhao Gou, Tom Ko, Hansi Yang, James T. Kwok, Yu Zhang, Mingxuan Wang
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 A* conf
Multi-Objective Deep Learning with Adaptive Reference Vectors.
NeurIPS
Weiyu Chen, James T. Kwok
2022 J jnl
Pyramidal dense attention networks for single image super-resolution.
IET Image Process.
Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
2022 A conf
Query Rewriting in TaoBao Search.
CIKM
Sen Li, Fuyu Lv, Taiwei Jin, Guiyang Li, Yukun Zheng, Tao Zhuang, Qingwen Liu, Xiaoyi Zeng, James T. Kwok, Qianli Ma
2022 A* conf
Revisiting Over-smoothing in BERT from the Perspective of Graph.
ICLR
Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok
2022 J jnl
Revisiting Over-smoothing in BERT from the Perspective of Graph.
CoRR
Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok
2022 J jnl
Searching a High-Performance Feature Extractor for Text Recognition Network.
CoRR
Hui Zhang, Quanming Yao, James T. Kwok, Xiang Bai
2022 A* conf
Subspace Learning for Effective Meta-Learning.
ICML
Weisen Jiang, James T. Kwok, Yu Zhang
2021 A* conf
A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning.
WWW
Yaqing Wang, Quanming Yao, James T. Kwok
2021 — conf
Dropout's Dream Land: Generalization from Learned Simulators to Reality.
ECML/PKDD (1)
Zac Wellmer, James T. Kwok
2021 J jnl
Dropout's Dream Land: Generalization from Learned Simulators to Reality.
CoRR
Zac Wellmer, James T. Kwok
2021 A* conf
Effective Meta-Regularization by Kernelized Proximal Regularization.
NeurIPS
Weisen Jiang, James T. Kwok, Yu Zhang
2021 J jnl
Feedback Pyramid Attention Networks for Single Image Super-Resolution.
CoRR
Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
2021 J jnl
Generalizing from a Few Examples: A Survey on Few-shot Learning.
ACM Comput. Surv.
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni
2021 J jnl
Noniterative Sparse LS-SVM Based on Globally Representative Point Selection.
IEEE Trans. Neural Networks Learn. Syst.
Yuefeng Ma, Xun Liang, Gang Sheng, James T. Kwok, Maoli Wang, Guangshun Li
2021 J jnl
Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution.
CoRR
Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei
2021 B conf
SEEN: Few-Shot Classification with SElf-ENsemble.
IJCNN
Weisen Jiang, Yu Zhang, James T. Kwok
2021 J jnl
Side Information Fusion for Recommender Systems over Heterogeneous Information Network.
ACM Trans. Knowl. Discov. Data
Huan Zhao, Quanming Yao, Yangqiu Song, James T. Kwok, Dik Lun Lee
2021 J jnl
SparseBERT: Rethinking the Importance Analysis in Self-attention.
CoRR
Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James T. Kwok
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 J jnl
Tensorizing Subgraph Search in the Supernet.
CoRR
Hansi Yang, Quanming Yao, James T. Kwok
2021 A* conf
Time Series Anomaly Detection with Multiresolution Ensemble Decoding.
AAAI
Lifeng Shen, Zhongzhong Yu, Qianli Ma, James T. Kwok
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
Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys.
KDD
Rishabh Mehrotra, Ben Carterette, Yong Li, Quanming Yao, Chen Gao, James T. Kwok, Qiang Yang, Isabelle Guyon
2020 A* conf
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS.
NeurIPS
Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang
2020 A* conf
Effective Decoding in Graph Auto-Encoder Using Triadic Closure.
AAAI
Han Shi, Haozheng Fan, James T. Kwok
2020 J jnl
Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization.
CoRR
Yaqing Wang, Quanming Yao, James T. Kwok
2020 A* conf
Efficient Neural Interaction Function Search for Collaborative Filtering.
WWW
Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li, Cho-Jui Hsieh
2020 J jnl
Generalized Convolutional Sparse Coding With Unknown Noise.
IEEE Trans. Image Process.
Yaqing Wang, James T. Kwok, Lionel M. Ni
2020 — ed.
Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part IV
ICONIP (4)
Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
2020 — ed.
Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part V
ICONIP (5)
Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
2020 — ed.
Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part I
ICONIP (1)
Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
2020 — ed.
Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part II
ICONIP (2)
Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
2020 — ed.
Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part III
ICONIP (3)
Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
2020 — ch.
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
Federated Learning
Xiawei Guo, Quanming Yao, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang
2020 A* conf
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network.
NeurIPS
Lifeng Shen, Zhuocong Li, James T. Kwok
2019 J jnl
Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion.
IEEE Trans. Knowl. Data Eng.
Quanming Yao, James T. Kwok
2019 — conf
Analysis of Quantized Models.
ICLR (Poster)
Lu Hou, Ruiliang Zhang, James T. Kwok
2019 J jnl
Blockwise Adaptivity: Faster Training and Better Generalization in Deep Learning.
CoRR
Shuai Zheng, James T. Kwok
2019 A* conf
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback.
NeurIPS
Shuai Zheng, Ziyue Huang, James T. Kwok
2019 J jnl
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback.
CoRR
Shuai Zheng, Ziyue Huang, James T. Kwok
2019 B conf
Dynamic Unit Surgery for Deep Neural Network Compression and Acceleration.
IJCNN
Minsam Kim, James T. Kwok
2019 J jnl
Effective Decoding in Graph Auto-Encoder using Triadic Closure.
CoRR
Han Shi, Haozheng Fan, James T. Kwok
2019 J jnl
General Convolutional Sparse Coding with Unknown Noise.
CoRR
Yaqing Wang, James T. Kwok, Lionel M. Ni
2019 J jnl
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers.
IEEE Trans. Pattern Anal. Mach. Intell.
Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu
2019 J jnl
Low-Rank Matrix Learning Using Biconvex Surrogate Minimization.
IEEE Trans. Neural Networks Learn. Syst.
En-Liang Hu, James T. Kwok
2019 J jnl
Multi-objective Neural Architecture Search via Predictive Network Performance Optimization.
CoRR
Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang
2019 A* conf
Normalization Helps Training of Quantized LSTM.
NeurIPS
Lu Hou, Jinhua Zhu, James T. Kwok, Fei Gao, Tao Qin, Tie-Yan Liu
2019 — conf
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space.
ECML/PKDD (3)
Zac Wellmer, James T. Kwok
2019 J jnl
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space.
CoRR
Zac Wellmer, James T. Kwok
2019 A* conf
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
IJCAI
Quanming Yao, Xiawei Guo, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang
2019 J jnl
Searching for Interaction Functions in Collaborative Filtering.
CoRR
Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li
2018 J jnl
Corrigendum to "Multi-label learning in the independent label sub-spaces" [Pattern Recognition Letters 97(2017) 8-12].
Pattern Recognit. Lett.
Elham J. Barezi, James T. Kwok, Hamid R. Rabiee
2018 J jnl
Fast-Solving Quasi-Optimal LS-S
IEEE Trans. Neural Networks Learn. Syst.
Yuefeng Ma, Xun Liang, James T. Kwok, Jianping Li, Xiaoping Zhou, Haiyan Zhang
2018 J jnl
Learning with Heterogeneous Side Information Fusion for Recommender Systems.
CoRR
Huan Zhao, Quanming Yao, Yangqiu Song, James T. Kwok, Dik Lun Lee
2018 J jnl
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data.
CoRR
Shuai Zheng, James T. Kwok
2018 — conf
Loss-aware Weight Quantization of Deep Networks.
ICLR (Poster)
Lu Hou, James T. Kwok
2018 J jnl
Loss-aware Weight Quantization of Deep Networks.
CoRR
Lu Hou, James T. Kwok
2018 J jnl
Multi-Label Learning with Global and Local Label Correlation.
IEEE Trans. Knowl. Data Eng.
Yue Zhu, James T. Kwok, Zhi-Hua Zhou
2018 J jnl
Online Convolutional Sparse Coding with Sample-Dependent Dictionary.
CoRR
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni
2018 J jnl
Power Law in Sparsified Deep Neural Networks.
CoRR
Lu Hou, James T. Kwok
2018 J jnl
Scalable Online Convolutional Sparse Coding.
IEEE Trans. Image Process.
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni
2018 A* conf
Scalable Robust Matrix Factorization with Nonconvex Loss.
NeurIPS
Quanming Yao, James T. Kwok
2017 J jnl
Accelerated and Inexact Soft-Impute for Large-Scale Matrix and Tensor Completion.
CoRR
Quanming Yao, James T. Kwok
2017 A* conf
Collaborative Filtering with Social Local Models.
ICDM
Huan Zhao, Quanming Yao, James T. Kwok, Dik Lun Lee
2017 A* conf
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
IJCAI
Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu
2017 J jnl
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
J. Mach. Learn. Res.
Quanming Yao, James T. Kwok
2017 A* conf
Follow the Moving Leader in Deep Learning.
ICML
Shuai Zheng, James T. Kwok
2017 J jnl
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers.
CoRR
Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu
2017 — conf
Loss-aware Binarization of Deep Networks.
ICLR (Poster)
Lu Hou, Quanming Yao, James T. Kwok
2017 J jnl
Multi-Label Learning with Global and Local Label Correlation.
CoRR
Yue Zhu, James T. Kwok, Zhi-Hua Zhou
2017 J jnl
Multi-Label learning in the independent label sub-spaces.
Pattern Recognit. Lett.
Elham J. Barezi, James T. Kwok, Hamid R. Rabiee
2017 J jnl
Online Convolutional Sparse Coding.
CoRR
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni
2017 B conf
Zero-shot learning with a partial set of observed attributes.
IJCNN
Yaqing Wang, James T. Kwok, Quanming Yao, Lionel M. Ni
2016 — conf
Aggregating Crowdsourced Ordinal Labels via Bayesian Clustering.
ECML/PKDD (1)
Xiawei Guo, James T. Kwok
2016 A* conf
Asynchronous Distributed Semi-Stochastic Gradient Optimization.
AAAI
Ruiliang Zhang, Shuai Zheng, James T. Kwok
2016 A* conf
Efficient Learning of Timeseries Shapelets.
AAAI
Lu Hou, James T. Kwok, Jacek M. Zurada
2016 A* conf
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
ICML
Quanming Yao, James T. Kwok
2016 J jnl
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
CoRR
Quanming Yao, James T. Kwok
2016 J jnl
Fast Learning with Nonconvex L1-2 Regularization.
CoRR
Quanming Yao, James T. Kwok
2016 A* conf
Fast Nonsmooth Regularized Risk Minimization with Continuation.
AAAI
Shuai Zheng, Ruiliang Zhang, James T. Kwok
2016 A* conf
Fast-and-Light Stochastic ADMM.
IJCAI
Shuai Zheng, James T. Kwok
2016 J jnl
Fast-and-Light Stochastic ADMM.
CoRR
Shuai Zheng, James T. Kwok
2016 A* conf
Greedy Learning of Generalized Low-Rank Models.
IJCAI
Quanming Yao, James T. Kwok
2016 J jnl
Learning of Generalized Low-Rank Models: A Greedy Approach.
CoRR
Quanming Yao, James T. Kwok
2016 J jnl
Loss-aware Binarization of Deep Networks.
CoRR
Lu Hou, Quanming Yao, James T. Kwok
2016 J jnl
Special issue: First International Conference on Big Data and Smart Computing (BigComp2014).
Data Knowl. Eng.
Jinho Kim, James T. Kwok, Kazutoshi Sumiya, Byoung-Tak Zhang
2016 A* conf
Towards Safe Semi-Supervised Learning for Multivariate Performance Measures.
AAAI
Yufeng Li, James T. Kwok, Zhi-Hua Zhou
2015 A* conf
Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion.
IJCAI
Quanming Yao, James T. Kwok
2015 J jnl
Bayes-Optimal Hierarchical Multilabel Classification.
IEEE Trans. Knowl. Data Eng.
Wei Bi, James T. Kwok
2015 B conf
Collaborative filtering via co-factorization of individuals and groups.
IJCNN
Yihai Huang, James T. Kwok
2015 A* conf
Colorization by Patch-Based Local Low-Rank Matrix Completion.
AAAI
Quanming Yao, James T. Kwok
2015 J jnl
Fast Distributed Asynchronous SGD with Variance Reduction.
CoRR
Ruiliang Zhang, Shuai Zheng, James T. Kwok
2015 A* conf
Fast Low-Rank Matrix Learning with Nonconvex Regularization.
ICDM
Quanming Yao, James T. Kwok, Wenliang Zhong
2015 — conf
Fast Second Order Stochastic Backpropagation for Variational Inference.
NIPS
Kai Fan, Ziteng Wang, Jeffrey M. Beck, James T. Kwok, Katherine A. Heller
2015 J jnl
Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD.
IEEE Trans. Neural Networks Learn. Syst.
Mu Li, Wei Bi, James T. Kwok, Bao-Liang Lu
2015 J jnl
Scalable Nonparametric Low-Rank Kernel Learning Using Block Coordinate Descent.
IEEE Trans. Neural Networks Learn. Syst.
En-Liang Hu, James T. Kwok
2015 J jnl
Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Networks Learn. Syst.
Kai Zhang, Liang Lan, James T. Kwok, Slobodan Vucetic, Bahram Parvin
2014 A* conf
Accurate Integration of Aerosol Predictions by Smoothing on a Manifold.
AAAI
Shuai Zheng, James T. Kwok
2014 A* conf
Asynchronous Distributed ADMM for Consensus Optimization.
ICML
Ruiliang Zhang, James T. Kwok
2014 A* conf
Gradient Descent with Proximal Average for Nonconvex and Composite Regularization.
AAAI
Wenliang Zhong, James T. Kwok
2014 A conf
Learning to Predict from Crowdsourced Data.
UAI
Wei Bi, Liwei Wang, James T. Kwok, Zhuowen Tu
2014 J jnl
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
IEEE Trans. Neural Networks Learn. Syst.
Wei Bi, James T. Kwok
2014 A* conf
Multilabel Classification with Label Correlations and Missing Labels.
AAAI
Wei Bi, James T. Kwok
2014 J jnl
Selected papers from the 2011 International Conference on Neural Information Processing (ICONIP 2011).
Neurocomputing
James T. Kwok, Liqing Zhang, Hongtao Lu
2014 J jnl
Simple randomized algorithms for online learning with kernels.
Neural Networks
Wenwu He, James T. Kwok
2013 A* conf
Accurate Probability Calibration for Multiple Classifiers.
IJCAI
Wenliang Zhong, James T. Kwok
2013 J jnl
Convex and Scalable Weakly Labeled SVMs
CoRR
Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou
2013 J jnl
Convex and scalable weakly labeled SVMs.
J. Mach. Learn. Res.
Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou
2013 A* conf
Efficient Kernel Learning from Side Information Using ADMM.
IJCAI
En-Liang Hu, James T. Kwok
2013 A* conf
Efficient Learning for Models with DAG-Structured Parameter Constraints.
ICDM
Leon Wenliang Zhong, James T. Kwok
2013 J jnl
Fast Stochastic Alternating Direction Method of Multipliers.
CoRR
Leon Wenliang Zhong, James T. Kwok
2013 — conf
Flexible Nonparametric Kernel Learning with Different Loss Functions.
ICONIP (2)
En-Liang Hu, James T. Kwok
2013 — conf
Learning from High-Dimensional Data in Multitask/Multilabel Classification.
ACPR
James T. Kwok
2012 J jnl
Bilinear Probabilistic Principal Component Analysis.
IEEE Trans. Neural Networks Learn. Syst.
Jianhua Zhao, Philip L. H. Yu, James T. Kwok
2012 J jnl
Efficient Sparse Modeling With Automatic Feature Grouping.
IEEE Trans. Neural Networks Learn. Syst.
Leon Wenliang Zhong, James T. Kwok
2012 A* conf
Hierarchical Multilabel Classification with Minimum Bayes Risk.
ICDM
Wei Bi, James T. Kwok
2012 — conf
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification.
NIPS
Wei Bi, James T. Kwok
2011 J jnl
Domain Adaptation via Transfer Component Analysis.
IEEE Trans. Neural Networks
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang
2011 A* conf
Efficient Sparse Modeling with Automatic Feature Grouping.
ICML
Wenliang Zhong, James T. Kwok
2011 J jnl
Incorporating cellular sorting structure for better prediction of protein subcellular locations.
J. Exp. Theor. Artif. Intell.
Wen-Yun Yang, Bao-Liang Lu, James T. Kwok
2011 A* conf
MultiLabel Classification on Tree- and DAG-Structured Hierarchies.
ICML
Wei Bi, James T. Kwok
2011 — ed.
Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part I
ICONIP (1)
Bao-Liang Lu, Liqing Zhang, James T. Kwok
2011 — ed.
Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part II
ICONIP (2)
Bao-Liang Lu, Liqing Zhang, James T. Kwok
2011 — ed.
Neural Information Processing - 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011, Proceedings, Part III
ICONIP (3)
Bao-Liang Lu, Liqing Zhang, James T. Kwok
2011 B conf
Structured clustering with automatic kernel adaptation.
IJCNN
Weike Pan, James T. Kwok
2011 A* conf
Time and space efficient spectral clustering via column sampling.
CVPR
Mu Li, Xiao-Chen Lian, James T. Kwok, Bao-Liang Lu
2010 J jnl
Clustered Nyström method for large scale manifold learning and dimension reduction.
IEEE Trans. Neural Networks
Kai Zhang, James T. Kwok
2010 A* conf
Cost-Sensitive Semi-Supervised Support Vector Machine.
AAAI
Yufeng Li, James T. Kwok, Zhi-Hua Zhou
2010 J jnl
Fast and accurate kernel density approximation using a divide-and-conquer approach.
J. Zhejiang Univ. Sci. C
Yan-xia Jin, Kai Zhang, James T. Kwok, Han-chang Zhou
2010 J jnl
Incorporating the loss function into discriminative clustering of structured outputs.
IEEE Trans. Neural Networks
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. Tsang
2010 A* conf
Making Large-Scale Nyström Approximation Possible.
ICML
Mu Li, James T. Kwok, Bao-Liang Lu
2010 B conf
Manifold regularization for structured outputs via the joint kernel.
IJCNN
Chonghai Hu, James T. Kwok
2010 A* conf
Online multiple instance learning with no regret.
CVPR
Mu Li, James T. Kwok, Bao-Liang Lu
2010 J jnl
Simplifying mixture models through function approximation.
IEEE Trans. Neural Networks
Kai Zhang, James T. Kwok
2010 A conf
Spectral and Semidefinite Relaxation of the CLUHSIC Algorithm.
SDM
Wen-Yun Yang, James T. Kwok, Bao-Liang Lu
2009 — conf
A Convex Method for Locating Regions of Interest with Multi-instance Learning.
ECML/PKDD (2)
Yufeng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou
2009 A* conf
Accelerated Gradient Method for Multi-task Sparse Learning Problem.
ICDM
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell
2009 — conf
Accelerated Gradient Methods for Stochastic Optimization and Online Learning.
NIPS
Chonghai Hu, James T. Kwok, Weike Pan
2009 J jnl
Density-Weighted Nyström Method for Computing Large Kernel Eigensystems.
Neural Comput.
Kai Zhang, James T. Kwok
2009 A* conf
Domain Adaptation via Transfer Component Analysis.
IJCAI
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang
2009 J jnl
Maximum Margin Clustering Made Practical.
IEEE Trans. Neural Networks
Kai Zhang, Ivor W. Tsang, James T. Kwok
2009 A conf
Multiple Kernel Clustering.
SDM
Bin Zhao, James T. Kwok, Changshui Zhang
2009 A* conf
Prototype vector machine for large scale semi-supervised learning.
ICML
Kai Zhang, James T. Kwok, Bahram Parvin
2009 A* conf
Semi-supervised learning using label mean.
ICML
Yufeng Li, James T. Kwok, Zhi-Hua Zhou
2008 A* conf
Improved Nyström low-rank approximation and error analysis.
ICML
Kai Zhang, Ivor W. Tsang, James T. Kwok
2008 J jnl
Matrix-Variate Factor Analysis and Its Applications.
IEEE Trans. Neural Networks
Xianchao Xie, Shuicheng Yan, James T. Kwok, Thomas S. Huang
2008 A* conf
Transfer Learning via Dimensionality Reduction.
AAAI
Sinno Jialin Pan, James T. Kwok, Qiang Yang
2008 A* conf
Transferring Localization Models across Space.
AAAI
Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. Kwok
2007 J jnl
A Class of Single-Class Minimax Probability Machines for Novelty Detection.
IEEE Trans. Neural Networks
James T. Kwok, Ivor Wai-Hung Tsang, Jacek M. Zurada
2007 A* conf
Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning.
AAAI
Sinno Jialin Pan, James T. Kwok, Qiang Yang, Jeffrey Junfeng Pan
2007 J jnl
End-to-end privacy control in service outsourcing of human intensive processes: A multi-layered Web service integration approach.
Inf. Syst. Frontiers
Patrick C. K. Hung, Dickson K. W. Chiu, W. W. Fung, William K. Cheung, Raymond K. Wong, Samuel P. M. Choi, Eleanna Kafeza, James T. Kwok, Joshua C. C. Pun, Vivying S. Y. Cheng
2007 A* conf
Ensembles of Partially Trained SVMs with Multiplicative Updates.
IJCAI
Ivor W. Tsang, James T. Kwok
2007 J jnl
Face recognition using spectral features.
Pattern Recognit.
Fei Wang, Jingdong Wang, Changshui Zhang, James T. Kwok
2007 A* conf
Marginalized Multi-Instance Kernels.
IJCAI
James T. Kwok, Pak-Ming Cheung
2007 A* conf
Maximum margin clustering made practical.
ICML
Kai Zhang, Ivor W. Tsang, James T. Kwok
2007 J jnl
SVDD-Based Pattern Denoising.
Neural Comput.
Jooyoung Park, Daesung Kang, Jongho Kim, James T. Kwok, Ivor W. Tsang
2007 A* conf
Simpler core vector machines with enclosing balls.
ICML
Ivor W. Tsang, András Kocsor, James T. Kwok
2007 J jnl
Surrogate maximization/minimization algorithms and extensions.
Mach. Learn.
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
2006 J jnl
A novel incremental principal component analysis and its application for face recognition.
IEEE Trans. Syst. Man Cybern. Part B
Haitao Zhao, Pong Chi Yuen, James T. Kwok
2006 A* conf
A regularization framework for multiple-instance learning.
ICML
Pak-Ming Cheung, James T. Kwok
2006 — conf
Accelerated Convergence Using Dynamic Mean Shift.
ECCV (2)
Kai Zhang, James T. Kwok, Ming Tang
2006 A* conf
Block-quantized kernel matrix for fast spectral embedding.
ICML
Kai Zhang, James T. Kwok
2006 — conf
Diversified SVM Ensembles for Large Data Sets.
ECML
Ivor W. Tsang, András Kocsor, James T. Kwok
2006 B conf
Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers.
IJCNN
Ken Chen, Bao-Liang Lu, James T. Kwok
2006 A* conf
Efficient kernel feature extraction for massive data sets.
KDD
Ivor W. Tsang, András Kocsor, James T. Kwok
2006 J jnl
Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting.
IEEE Trans. Speech Audio Process.
Brian Kan-Wing Mak, Roger Wend-Huu Hsiao, Simon Ka-Lung Ho, James T. Kwok
2006 — conf
Facial Image Reconstruction by SVDD-Based Pattern De-noising.
ICB
Jooyoung Park, Daesung Kang, James T. Kwok, Sang-Woong Lee, Bon-Woo Hwang, Seong-Whan Lee
2006 — conf
Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression.
ICASSP (1)
Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey Junfeng Pan
2006 — conf
Gene Feature Extraction Using T-Test Statistics and Kernel Partial Least Squares.
ICONIP (3)
Shutao Li, Chen Liao, James T. Kwok
2006 — conf
Large-Scale Sparsified Manifold Regularization.
NIPS
Ivor W. Tsang, James T. Kwok
2006 B conf
Learning the Kernel in Mahalanobis One-Class Support Vector Machines.
IJCNN
Ivor W. Tsang, James T. Kwok, Shutao Li
2006 A* conf
Locally adaptive classification piloted by uncertainty.
ICML
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwok
2006 J jnl
Model-based transductive learning of the kernel matrix.
Mach. Learn.
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
2006 J jnl
Multidimensional Vector Regression for Accurate and Low-Cost Location Estimation in Pervasive Computing.
IEEE Trans. Knowl. Data Eng.
Jeffrey Junfeng Pan, James T. Kwok, Qiang Yang, Yiqiang Chen
2006 — conf
Multimodal Registration using the Discrete Wavelet Frame Transform.
ICPR (3)
Shutao Li, Jinglin Peng, James T. Kwok, Jing Zhang
2006 — conf
Simplifying Mixture Models through Function Approximation.
NIPS
Kai Zhang, James T. Kwok
2006 — ed.
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2006 and SPR 2006, Hong Kong, China, August 17-19, 2006, Proceedings
SSPR/SPR
Dit-Yan Yeung, James T. Kwok, Ana L. N. Fred, Fabio Roli, Dick de Ridder
2006 B conf
Wavelet-Based Feature Extraction for Microarray Data Classification.
IJCNN
Shutao Li, Chen Liao, James T. Kwok
2005 A* conf
Accurate and Low-cost Location Estimation Using Kernels.
IJCAI
Jeffrey Junfeng Pan, James T. Kwok, Qiang Yang, Yiqiang Chen
2005 — conf
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation.
CVPR (2)
Kai Zhang, Ming Tang, James T. Kwok
2005 J jnl
Core Vector Machines: Fast SVM Training on Very Large Data Sets.
J. Mach. Learn. Res.
Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung
2005 A* conf
Core Vector Regression for very large regression problems.
ICML
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
2005 B conf
Data-dependent kernels for high-dimensional data classification.
IJCNN
Jingdong Wang, James T. Kwok, Helen C. Shen, Long Quan
2005 B conf
Position estimation for wireless sensor networks.
GLOBECOM
Kin Fung Simon Wong, Ivor W. Tsang, Victor Cheung, S.-H. Gary Chan, James T. Kwok
2005 C conf
Towards end-to-end privacy control in the outsourcing of marketing activities: a web service integration solution.
ICEC
Patrick C. K. Hung, Dickson K. W. Chiu, W. W. Fung, William K. Cheung, Raymond K. Wong, Samuel P. M. Choi, Eleanna Kafeza, James T. Kwok, Joshua C. C. Pun, Vivying S. Y. Cheng
2004 — conf
A study of various composite kernels for kernel eigenvoice speaker adaptation.
ICASSP (1)
Brian Mak, James T. Kwok, Simon Ka-Lung Ho
2004 A* conf
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo.
AAAI
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan Yeung
2004 A* conf
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm.
ICML
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
2004 J jnl
Dissimilarity learning for nominal data.
Pattern Recognit.
Victor Cheng, Chun Hung Li, James T. Kwok, Chi-Kwong Li
2004 — conf
Efficient Hyperkernel Learning Using Second-Order Cone Programming.
ECML
Ivor W. Tsang, James T. Kwok
2004 C conf
Incremental PCA based face recognition.
ICARCV
Haitao Zhao, Pong Chi Yuen, James T. Kwok, Jingyu Yang
2004 B conf
Scaling up support vector data description by using core-sets.
IJCNN
Calvin S. Chu, Ivor W. Tsang, James T. Kwok
2004 A conf
Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA.
INTERSPEECH
Brian Mak, Simon Ka-Lung Ho, James T. Kwok
2004 A* conf
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model.
ICML
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
2003 — conf
Eigenvoice Speaker Adaptation via Composite Kernel PCA.
NIPS
James T. Kwok, Brian Mak, Simon Ka-Lung Ho
2003 A* conf
Learning with Idealized Kernels.
ICML
James T. Kwok, Ivor W. Tsang
2003 J jnl
Linear dependency between ε and the input noise in ε-support vector regression.
IEEE Trans. Neural Networks
James T. Kwok, Ivor W. Tsang
2003 J jnl
Mining customer product ratings for personalized marketing.
Decis. Support Syst.
Kwok-Wai Cheung, James T. Kwok, Martin H. C. Law, Kwok Ching Tsui
2003 A* conf
Parametric Distance Metric Learning with Label Information.
IJCAI
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
2003 J jnl
Texture classification using the support vector machines.
Pattern Recognit.
Shutao Li, James T. Kwok, Hailong Zhu, Yaonan Wang
2003 A* conf
The Pre-Image Problem in Kernel Methods.
ICML
James T. Kwok, Ivor W. Tsang
2002 C conf
Fusing Images with Multiple Focuses Using Support Vector Machines.
ICANN
Shutao Li, James T. Kwok, Yaonan Wang
2002 — conf
Improving De-Noising by Coefficient De-Noising and Dyadic Wavelet Transform.
ICPR (2)
Hailong Zhu, James T. Kwok, Liangsheng Qu
2002 J jnl
Multifocus image fusion using artificial neural networks.
Pattern Recognit. Lett.
Shutao Li, James T. Kwok, Yaonan Wang
2002 J jnl
Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images.
Inf. Fusion
Shutao Li, James T. Kwok, Yaonan Wang
2001 — conf
Applying the Bayesian Evidence Framework to \nu -Support Vector Regression.
ECML
Martin H. C. Law, James T. Kwok
2001 J jnl
Combination of images with diverse focuses using the spatial frequency.
Inf. Fusion
Shutao Li, James T. Kwok, Yaonan Wang
2001 C conf
Linear Dependency between epsilon and the Input Noise in epsilon-Support Vector Regression.
ICANN
James T. Kwok
2000 B conf
Rival Penalized Competitive Learning for Model-Based Sequence Clustering.
ICPR
Martin H. C. Law, James T. Kwok