Tsang, Ivor

43 publications

ICML 2025 Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction Yadong Sun, Xiaofeng Cao, Ivor Tsang, Heng Tao Shen

NeurIPS 2025 AngleRoCL: Angle-Robust Concept Learning for Physically View-Invariant Adversarial Patches Wenjun Ji, Yuxiang Fu, Luyang Ying, Deng-Ping Fan, Yuyi Wang, Ming-Ming Cheng, Ivor Tsang, Qing Guo

ICLR 2025 Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration Heyang Zhao, Xingrui Yu, David Mark Bossens, Ivor Tsang, Quanquan Gu

NeurIPS 2025 DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches Yun Xing, Yue Cao, Nhat Chung, Jie Zhang, Ivor Tsang, Ming-Ming Cheng, Yang Liu, Lei Ma, Qing Guo

ICML 2025 Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor Tsang

ICLRW 2025 Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals Cheng Chen, Haiyan Yin, Ivor Tsang

ICLR 2025 Fast Direct: Query-Efficient Online Black-Box Guidance for Diffusion-Model Target Generation Kim Yong Tan, Yueming Lyu, Ivor Tsang, Yew-Soon Ong

TMLR 2025 Graph Potential Field Neural Network for Massive Agents Group-Wise Path Planning Yueming Lyu, Xiaowei Zhou, Xingrui Yu, Ivor Tsang

NeurIPS 2025 InstructFlow: Adaptive Symbolic Constraint-Guided Code Generation for Long-Horizon Planning Haotian Chi, Zeyu Feng, Yueming Lyu, Chengqi Zheng, Linbo Luo, Yew-Soon Ong, Ivor Tsang, Hechang Chen, Yi Chang, Haiyan Yin

ICLRW 2025 LLMV-AgE: Verifying LLM-Guided Planning for Agentic Exploration in Open-World RL Haotian Chi, Songwei Zhao, Ivor Tsang, Yew-Soon Ong, Hechang Chen, Yi Chang, Haiyan Yin

ICLRW 2025 Nonparametric Distributional Black-Box Optimization via Diffusion Process Yueming Lyu, Atsushi Nitanda, Ivor Tsang

ICLR 2025 ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor Tsang

CVPR 2025 SceneTAP: Scene-Coherent Typographic Adversarial Planner Against Vision-Language Models in Real-World Environments Yue Cao, Yun Xing, Jie Zhang, Di Lin, Tianwei Zhang, Ivor Tsang, Yang Liu, Qing Guo

ICLR 2025 Second-Order Fine-Tuning Without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor Tsang

ICLR 2025 Sharpness-Aware Black-Box Optimization Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor Tsang

ICLR 2025 Training-Free Dataset Pruning for Instance Segmentation Yalun Dai, Lingao Xiao, Ivor Tsang, Yang He

TMLR 2025 Unlearning Misalignment for Personalized LLM Adaptation via Instance-Response-Dependent Discrepancies Cheng Chen, Atsushi Nitanda, Ivor Tsang

ICLR 2024 Adaptive Stochastic Gradient Algorithm for Black-Box Multi-Objective Learning Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor Tsang

ECCV 2024 Boosting Transferability in Vision-Language Attacks via Diversification Along the Intersection Region of Adversarial Trajectory Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor Tsang, Qing Guo

ICML 2024 Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? Yilong Wang, Haishan Ye, Guang Dai, Ivor Tsang

ICLR 2024 Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor Tsang, Yong Liu

ICML 2024 Diversified Batch Selection for Training Acceleration Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor Tsang, Yanfeng Wang

ICML 2024 Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor Tsang

ICML 2024 Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems Without First-Order Gradient Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor Tsang

ICLR 2024 IRAD: Implicit Representation-Driven Image Resampling Against Adversarial Attacks Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor Tsang, Yang Liu, Qing Guo

ICLR 2024 Multisize Dataset Condensation Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor Tsang

ICLR 2024 On Harmonizing Implicit Subpopulations Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor Tsang, Ya Zhang, Yanfeng Wang

CPAL 2024 PC-X: Profound Clustering via Slow Exemplars Yuangang Pan, Yinghua Yao, Ivor Tsang

NeurIPS 2024 Parsimony or Capability? Decomposition Delivers Both in Long-Term Time Series Forecasting Jinliang Deng, Feiyang Ye, Du Yin, Xuan Song, Ivor Tsang, Hui Xiong

TMLR 2023 Contrastive Attraction and Contrastive Repulsion for Representation Learning Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou

ICCV 2023 Leveraging Inpainting for Single-Image Shadow Removal Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor Tsang, Song Wang

ICML 2023 Nonparametric Iterative Machine Teaching Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor Tsang, James Kwok

TMLR 2022 Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor Tsang

ACML 2021 Asian Conference on Machine Learning: Preface Vineeth N. Balasubramanian, Ivor Tsang

ICML 2020 Intrinsic Reward Driven Imitation Learning via Generative Model Xingrui Yu, Yueming Lyu, Ivor Tsang

ICML 2020 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor Tsang, Masashi Sugiyama

ICML 2019 How Does Disagreement Help Generalization Against Label Corruption? Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor Tsang, Masashi Sugiyama

NeurIPS 2018 Co-Teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama

NeurIPS 2018 Masking: A New Perspective of Noisy Supervision Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor Tsang, Ya Zhang, Masashi Sugiyama

NeurIPS 2017 Sparse Embedded $k$-Means Clustering Weiwei Liu, Xiaobo Shen, Ivor Tsang

NeurIPS 2015 On the Optimality of Classifier Chain for Multi-Label Classification Weiwei Liu, Ivor Tsang

ICCV 2013 Feature Weighting via Optimal Thresholding for Video Analysis Zhongwen Xu, Yi Yang, Ivor Tsang, Nicu Sebe, Alexander G. Hauptmann

AISTATS 2005 Very Large SVM Training Using Core Vector Machines Ivor Tsang, James Kwok, Pak-Ming Cheung