Yisen Wang - RankMe

237 papers A* 87A 3B 5C 1Misc 1Journal 135Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Autoregressive Models Rival Diffusion Models at ANY-ORDER Generation. CoRR Tianqi Du, Lizhe Fang, Weijie Yang, Chenheng Zhang, Zeming Wei, Yifei Wang, Yisen Wang
2026	J	`jnl`	Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD. CoRR Ze Peng, Jian Zhang, Yisen Wang, Lei Qi, Yinghuan Shi, Yang Gao
2026	J	`jnl`	ProcMEM: Learning Reusable Procedural Memory from Experience via Non-Parametric PPO for LLM Agents. CoRR Qirui Mi, Zhijian Ma, Mengyue Yang, Haoxuan Li, Yisen Wang, Haifeng Zhang, Jun Wang
2026	J	`jnl`	Rethinking Personalization in Large Language Models at the Token Level. CoRR Chenheng Zhang, Yijun Lu, Lizhe Fang, Chunyuan Zheng, Jiajun Chai, Xiaohan Wang, Guojun Yin, Wei Lin, Yisen Wang, Zhouchen Lin
2026	J	`jnl`	SAE as a Crystal Ball: Interpretable Features Predict Cross-domain Transferability of LLMs without Training. CoRR Qi Zhang, Yifei Wang, Xiaohan Wang, Jiajun Chai, Guojun Yin, Wei Lin, Yisen Wang
2025	J	`jnl`	Advancing LLM Safe Alignment with Safety Representation Ranking. CoRR Tianqi Du, Zeming Wei, Quan Chen, Chenheng Zhang, Yisen Wang
2025	J	`jnl`	An Augmentation Overlap Theory of Contrastive Learning. CoRR Qi Zhang, Yifei Wang, Yisen Wang
2025	J	`jnl`	An Augmentation Overlap Theory of Contrastive Learning. J. Mach. Learn. Res. Qi Zhang, Yifei Wang, Yisen Wang
2025	A*	`conf`	An Augmentation-Aware Theory for Self-Supervised Contrastive Learning. ICML Jingyi Cui, Hongwei Wen, Yisen Wang
2025	J	`jnl`	An Augmentation-Aware Theory for Self-Supervised Contrastive Learning. CoRR Jingyi Cui, Hongwei Wen, Yisen Wang
2025	J	`jnl`	An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise. CoRR Jingyi Cui, Yi-Ge Zhang, Hengyu Liu, Yisen Wang
2025	J	`jnl`	Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning. CoRR Ang Li, Yichuan Mo, Mingjie Li, Yifei Wang, Yisen Wang
2025	J	`jnl`	AttnGCG: Enhancing Jailbreaking Attacks on LLMs with Attention Manipulation. Trans. Mach. Learn. Res. Zijun Wang, Haoqin Tu, Jieru Mei, Bingchen Zhao, Yisen Wang, Cihang Xie
2025	A*	`conf`	Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness. ICLR Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang
2025	A*	`conf`	Can In-context Learning Really Generalize to Out-of-distribution Tasks? ICLR Qixun Wang, Yifei Wang, Xianghua Ying, Yisen Wang
2025	J	`jnl`	Decoding Large Language Diffusion Models with Foreseeing Movement. CoRR Yichuan Mo, Quan Chen, Mingjie Li, Zeming Wei, Yisen Wang
2025	J	`jnl`	G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning. CoRR Xiaojun Guo, Ang Li, Yifei Wang, Stefanie Jegelka, Yisen Wang
2025	J	`jnl`	Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training. CoRR Yisen Wang, Yichuan Mo, Hongjun Wang, Junyi Li, Zhouchen Lin
2025	A*	`conf`	Identifying and Understanding Cross-Class Features in Adversarial Training. ICML Zeming Wei, Steven Y. Guo, Yisen Wang
2025	J	`jnl`	Identifying and Understanding Cross-Class Features in Adversarial Training. CoRR Zeming Wei, Yiwen Guo, Yisen Wang
2025	A*	`conf`	Incorporating Arbitrary Matrix Group Equivariance into KANs. ICML Lexiang Hu, Yisen Wang, Zhouchen Lin
2025	J	`jnl`	Know When to Explore: Difficulty-Aware Certainty as a Guide for LLM Reinforcement Learning. CoRR Ang Li, Zhihang Yuan, Yang Zhang, Shouda Liu, Yisen Wang
2025	J	`jnl`	LANPO: Bootstrapping Language and Numerical Feedback for Reinforcement Learning in LLMs. CoRR Ang Li, Yifei Wang, Zhihang Yuan, Stefanie Jegelka, Yisen Wang
2025	J	`jnl`	Language Ranker: A Lightweight Ranking framework for LLM Decoding. CoRR Chenheng Zhang, Tianqi Du, Jizhe Zhang, Mingqing Xiao, Yifei Wang, Yisen Wang, Zhouchen Lin
2025	A*	`conf`	Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD. ICLR Ze Peng, Jian Zhang, Yisen Wang, Lei Qi, Yinghuan Shi, Yang Gao
2025	A*	`conf`	Long-Short Alignment for Effective Long-Context Modeling in LLMs. ICML Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang
2025	J	`jnl`	Long-Short Alignment for Effective Long-Context Modeling in LLMs. CoRR Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang
2025	J	`jnl`	Monet: Reasoning in Latent Visual Space Beyond Images and Language. CoRR Qixun Wang, Yang Shi, Yifei Wang, Yuanxing Zhang, Pengfei Wan, Kun Gai, Xianghua Ying, Yisen Wang
2025	J	`jnl`	On the Theoretical Understanding of Identifiable Sparse Autoencoders and Beyond. CoRR Jingyi Cui, Qi Zhang, Yifei Wang, Yisen Wang
2025	A*	`conf`	Projection Head is Secretly an Information Bottleneck. ICLR Zhuo Ouyang, Kaiwen Hu, Qi Zhang, Yifei Wang, Yisen Wang
2025	J	`jnl`	Projection Head is Secretly an Information Bottleneck. CoRR Zhuo Ouyang, Kaiwen Hu, Qi Zhang, Yifei Wang, Yisen Wang
2025	J	`jnl`	R^3-VQA: "Read the Room" by Video Social Reasoning. CoRR Lixing Niu, Jiapeng Li, Xingping Yu, Shu Wang, Ruining Feng, Bo Wu, Ping Wei, Yisen Wang, Lifeng Fan
2025	J	`jnl`	Recurrent Autoregressive Diffusion: Global Memory Meets Local Attention. CoRR Taiye Chen, Zihan Ding, Anjian Li, Christina Zhang, Zeqi Xiao, Yisen Wang, Chi Jin
2025	A*	`conf`	Rethinking Invariance in In-context Learning. ICLR Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang
2025	J	`jnl`	Rethinking Invariance in In-context Learning. CoRR Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang
2025	J	`jnl`	SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning. CoRR Xiaojun Guo, Runyu Zhou, Yifei Wang, Qi Zhang, Chenheng Zhang, Stefanie Jegelka, Xiaohan Wang, Jiajun Chai, Guojun Yin, Wei Lin, Yisen Wang
2025	A*	`conf`	SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation. ICLR Mingjie Li, Wai Man Si, Michael Backes, Yang Zhang, Yisen Wang
2025	J	`jnl`	SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation. CoRR Mingjie Li, Wai Man Si, Michael Backes, Yang Zhang, Yisen Wang
2025	J	`jnl`	Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval. CoRR Taiye Chen, Zeming Wei, Ang Li, Yisen Wang
2025	A*	`conf`	TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice. ICLR Shen Yan, Xingyan Bin, Sijun Zhang, Yisen Wang, Zhouchen Lin
2025	J	`jnl`	Towards provable probabilistic safety for scalable embodied AI systems. CoRR Linxuan He, Qing-Shan Jia, Ang Li, Hongyan Sang, Ling Wang, Jiwen Lu, Tao Zhang, Jie Zhou, Yi Zhang, Yisen Wang, Peng Wei, Zhongyuan Wang, Henry X. Liu, Shuo Feng
2025	J	`jnl`	Understanding Difficult-to-learn Examples in Contrastive Learning: A Theoretical Framework for Spectral Contrastive Learning. CoRR Yi-Ge Zhang, Jingyi Cui, Qiran Li, Yisen Wang
2025	A*	`conf`	What is Wrong with Perplexity for Long-context Language Modeling? ICLR Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka, Jinyang Gao, Bolin Ding, Yisen Wang
2025	J	`jnl`	When More is Less: Understanding Chain-of-Thought Length in LLMs. CoRR Yuyang Wu, Yifei Wang, Tianqi Du, Stefanie Jegelka, Yisen Wang
2024	A*	`conf`	A Canonicalization Perspective on Invariant and Equivariant Learning. NeurIPS George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
2024	J	`jnl`	A Canonization Perspective on Invariant and Equivariant Learning. CoRR George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
2024	A*	`conf`	A Theoretical Understanding of Self-Correction through In-context Alignment. NeurIPS Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang
2024	J	`jnl`	A Theoretical Understanding of Self-Correction through In-context Alignment. CoRR Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang
2024	J	`jnl`	AttnGCG: Enhancing Jailbreaking Attacks on LLMs with Attention Manipulation. CoRR Zijun Wang, Haoqin Tu, Jieru Mei, Bingchen Zhao, Yisen Wang, Cihang Xie
2024	J	`jnl`	Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness. CoRR Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang
2024	J	`jnl`	Can In-context Learning Really Generalize to Out-of-distribution Tasks? CoRR Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying
2024	A*	`conf`	Dissecting the Failure of Invariant Learning on Graphs. NeurIPS Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying
2024	J	`jnl`	Dissecting the Failure of Invariant Learning on Graphs. CoRR Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying
2024	A*	`conf`	Do Generated Data Always Help Contrastive Learning? ICLR Yifei Wang, Jizhe Zhang, Yisen Wang
2024	J	`jnl`	Do Generated Data Always Help Contrastive Learning? CoRR Yifei Wang, Jizhe Zhang, Yisen Wang
2024	J	`jnl`	EKAN: Equivariant Kolmogorov-Arnold Networks. CoRR Lexiang Hu, Yisen Wang, Zhouchen Lin
2024	J	`jnl`	FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs. CoRR Jinmin Li, Kuofeng Gao, Yang Bai, Jingyun Zhang, Shutao Xia, Yisen Wang
2024	A*	`conf`	Fight Back Against Jailbreaking via Prompt Adversarial Tuning. NeurIPS Yichuan Mo, Yuji Wang, Zeming Wei, Yisen Wang
2024	J	`jnl`	Generalization in Deep RL for TSP Problems via Equivariance and Local Search. SN Comput. Sci. Wenbin Ouyang, Yisen Wang, Paul Weng, Shaochen Han
2024	C	`conf`	Graph Neural Networks (with Proper Weights) Can Escape Oversmoothing. ACML Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang
2024	J	`jnl`	How to Craft Backdoors with Unlabeled Data Alone? CoRR Yifei Wang, Wenhan Ma, Stefanie Jegelka, Yisen Wang
2024	A*	`conf`	Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining. ICML Qi Zhang, Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang
2024	J	`jnl`	Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining. CoRR Qi Zhang, Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang
2024	J	`jnl`	MADE: Graph Backdoor Defense with Masked Unlearning. CoRR Xiao Lin, Mingjie Li, Yisen Wang
2024	A*	`conf`	Non-negative Contrastive Learning. ICLR Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang
2024	J	`jnl`	Non-negative Contrastive Learning. CoRR Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang
2024	J	`jnl`	On the Adversarial Transferability of Generalized "Skip Connections". CoRR Yisen Wang, Yichuan Mo, Dongxian Wu, Mingjie Li, Xingjun Ma, Zhouchen Lin
2024	A*	`conf`	On the Role of Discrete Tokenization in Visual Representation Learning. ICLR Tianqi Du, Yifei Wang, Yisen Wang
2024	J	`jnl`	On the Role of Discrete Tokenization in Visual Representation Learning. CoRR Tianqi Du, Yifei Wang, Yisen Wang
2024	A*	`conf`	PID: Prompt-Independent Data Protection Against Latent Diffusion Models. ICML Ang Li, Yichuan Mo, Mingjie Li, Yisen Wang
2024	J	`jnl`	PID: Prompt-Independent Data Protection Against Latent Diffusion Models. CoRR Ang Li, Yichuan Mo, Mingjie Li, Yisen Wang
2024	J	`jnl`	Sampling complex topology structures for spiking neural networks. Neural Networks Shen Yan, Qingyan Meng, Mingqing Xiao, Yisen Wang, Zhouchen Lin
2024	J	`jnl`	Studious Bob Fight Back Against Jailbreaking via Prompt Adversarial Tuning. CoRR Yichuan Mo, Yuji Wang, Zeming Wei, Yisen Wang
2024	A*	`conf`	TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors. ICML Yichuan Mo, Hui Huang, Mingjie Li, Ang Li, Yisen Wang
2024	J	`jnl`	TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors. CoRR Yichuan Mo, Hui Huang, Mingjie Li, Ang Li, Yisen Wang
2024	A*	`conf`	Understanding the Role of Equivariance in Self-supervised Learning. NeurIPS Yifei Wang, Kaiwen Hu, Sharut Gupta, Ziyu Ye, Yisen Wang, Stefanie Jegelka
2024	J	`jnl`	Understanding the Role of Equivariance in Self-supervised Learning. CoRR Yifei Wang, Kaiwen Hu, Sharut Gupta, Ziyu Ye, Yisen Wang, Stefanie Jegelka
2024	J	`jnl`	What is Wrong with Perplexity for Long-context Language Modeling? CoRR Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka, Jinyang Gao, Bolin Ding, Yisen Wang
2023	A*	`conf`	A Message Passing Perspective on Learning Dynamics of Contrastive Learning. ICLR Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
2023	J	`jnl`	A Message Passing Perspective on Learning Dynamics of Contrastive Learning. CoRR Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
2023	A*	`conf`	Adversarial Examples Are Not Real Features. NeurIPS Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang
2023	J	`jnl`	Adversarial Examples Are Not Real Features. CoRR Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang
2023	A*	`conf`	ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. ICLR Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang
2023	J	`jnl`	ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. CoRR Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang
2023	A*	`conf`	Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning. NeurIPS Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang
2023	J	`jnl`	Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning. CoRR Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang
2023	A*	`conf`	Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. NeurIPS Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang
2023	J	`jnl`	Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. CoRR Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang
2023	A*	`conf`	CFA: Class-Wise Calibrated Fair Adversarial Training. CVPR Zeming Wei, Yifei Wang, Yiwen Guo, Yisen Wang
2023	J	`jnl`	CFA: Class-wise Calibrated Fair Adversarial Training. CoRR Zeming Wei, Yifei Wang, Yiwen Guo, Yisen Wang
2023	A*	`conf`	ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond. ICLR Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang
2023	J	`jnl`	ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond. CoRR Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang
2023	J	`jnl`	Equilibrium Image Denoising With Implicit Differentiation. IEEE Trans. Image Process. Qi Chen, Yifei Wang, Zhengyang Geng, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2023	A*	`conf`	GEQ: Gaussian Kernel Inspired Equilibrium Models. NeurIPS Mingjie Li, Yisen Wang, Zhouchen Lin
2023	A*	`conf`	Generalist: Decoupling Natural and Robust Generalization. CVPR Hongjun Wang, Yisen Wang
2023	J	`jnl`	Generalist: Decoupling Natural and Robust Generalization. CoRR Hongjun Wang, Yisen Wang
2023	A*	`conf`	Identifiable Contrastive Learning with Automatic Feature Importance Discovery. NeurIPS Qi Zhang, Yifei Wang, Yisen Wang
2023	J	`jnl`	Identifiable Contrastive Learning with Automatic Feature Importance Discovery. CoRR Qi Zhang, Yifei Wang, Yisen Wang
2023	J	`jnl`	Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations. CoRR Zeming Wei, Yifei Wang, Yisen Wang
2023	A*	`conf`	Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. NeurIPS George Ma, Yifei Wang, Yisen Wang
2023	J	`jnl`	Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. CoRR Jiangyan Ma, Yifei Wang, Yisen Wang
2023	A*	`conf`	On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization. AAAI Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang
2023	A*	`conf`	On the Generalization of Multi-modal Contrastive Learning. ICML Qi Zhang, Yifei Wang, Yisen Wang
2023	J	`jnl`	On the Generalization of Multi-modal Contrastive Learning. CoRR Qi Zhang, Yifei Wang, Yisen Wang
2023	J	`jnl`	Query efficient black-box adversarial attack on deep neural networks. Pattern Recognit. Yang Bai, Yisen Wang, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia
2023	A*	`conf`	Rethinking Weak Supervision in Helping Contrastive Learning. ICML Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang
2023	J	`jnl`	Rethinking Weak Supervision in Helping Contrastive Learning. CoRR Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang
2023	A*	`conf`	Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning. ICLR Rundong Luo, Yifei Wang, Yisen Wang
2023	J	`jnl`	Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning. CoRR Rundong Luo, Yifei Wang, Yisen Wang
2023	J	`jnl`	Robust Long-Tailed Learning via Label-Aware Bounded CVaR. CoRR Hong Zhu, Runpeng Yu, Xing Tang, Yifei Wang, Yuan Fang, Yisen Wang
2023	J	`jnl`	SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks. CoRR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
2023	J	`jnl`	SPIDE: A purely spike-based method for training feedback spiking neural networks. Neural Networks Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
2023	J	`jnl`	Towards Control-Centric Representations in Reinforcement Learning from Images. CoRR Chen Liu, Hongyu Zang, Xin Li, Yong Heng, Yifei Wang, Zhen Fang, Yisen Wang, Mingzhong Wang
2023	A*	`conf`	Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks. ICCV Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
2023	J	`jnl`	Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks. CoRR Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
2023	A*	`conf`	Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism. ICLR Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang
2023	J	`jnl`	Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism. CoRR Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang
2023	A*	`conf`	Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States. ICLR Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin
2022	A*	`conf`	A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. ICLR Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	J	`jnl`	A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. CoRR Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	A*	`conf`	CerDEQ: Certifiable Deep Equilibrium Model. ICML Mingjie Li, Yisen Wang, Zhouchen Lin
2022	A*	`conf`	Certified Adversarial Robustness Under the Bounded Support Set. ICML Yiwen Kou, Qinyuan Zheng, Yisen Wang
2022	A*	`conf`	Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. ICLR Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	J	`jnl`	Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. CoRR Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	B	`conf`	Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium. IEEE Big Data Qi Chen, Yifei Wang, Yisen Wang, Jianlong Chang, Qi Tian, Jiansheng Yang, Zhouchen Lin
2022	A*	`conf`	G ICML Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin
2022	A*	`conf`	How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. NeurIPS Qi Zhang, Yifei Wang, Yisen Wang
2022	J	`jnl`	How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. CoRR Qi Zhang, Yifei Wang, Yisen Wang
2022	A*	`conf`	Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors. NeurIPS Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang
2022	J	`jnl`	Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors. CoRR Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang
2022	J	`jnl`	On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization. CoRR Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang
2022	A*	`conf`	Optimization inspired Multi-Branch Equilibrium Models. ICLR Mingjie Li, Yisen Wang, Xingyu Xie, Zhouchen Lin
2022	A*	`conf`	Optimization-Induced Graph Implicit Nonlinear Diffusion. ICML Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	J	`jnl`	Optimization-Induced Graph Implicit Nonlinear Diffusion. CoRR Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2022	J	`jnl`	Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability. CoRR Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
2022	J	`jnl`	Self-Ensemble Adversarial Training for Improved Robustness. CoRR Hongjun Wang, Yisen Wang
2022	A*	`conf`	Self-ensemble Adversarial Training for Improved Robustness. ICLR Hongjun Wang, Yisen Wang
2022	A*	`conf`	Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CVPR Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
2022	J	`jnl`	Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CoRR Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
2022	J	`jnl`	Training much deeper spiking neural networks with a small number of time-steps. Neural Networks Qingyan Meng, Shen Yan, Mingqing Xiao, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
2022	A*	`conf`	When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. NeurIPS Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang
2022	J	`jnl`	When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. CoRR Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang
2021	A*	`conf`	A Unified Approach to Interpreting and Boosting Adversarial Transferability. ICLR Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
2021	J	`jnl`	Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions. CoRR Nodens Koren, Qiuhong Ke, Yisen Wang, James Bailey, Xingjun Ma
2021	A*	`conf`	Adversarial Neuron Pruning Purifies Backdoored Deep Models. NeurIPS Dongxian Wu, Yisen Wang
2021	J	`jnl`	Adversarial Neuron Pruning Purifies Backdoored Deep Models. CoRR Dongxian Wu, Yisen Wang
2021	A*	`conf`	Analysis and Applications of Class-wise Robustness in Adversarial Training. KDD Qi Tian, Kun Kuang, Kelu Jiang, Fei Wu, Yisen Wang
2021	J	`jnl`	Analysis and Applications of Class-wise Robustness in Adversarial Training. CoRR Qi Tian, Kun Kuang, Kelu Jiang, Fei Wu, Yisen Wang
2021	A*	`conf`	Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
2021	J	`jnl`	Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
2021	J	`jnl`	Clustering Effect of (Linearized) Adversarial Robust Models. CoRR Yang Bai, Xin Yan, Yong Jiang, Shu-Tao Xia, Yisen Wang
2021	A*	`conf`	Clustering Effect of Adversarial Robust Models. NeurIPS Yang Bai, Xin Yan, Yong Jiang, Shu-Tao Xia, Yisen Wang
2021	A*	`conf`	Dissecting the Diffusion Process in Linear Graph Convolutional Networks. NeurIPS Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	J	`jnl`	Dissecting the Diffusion Process in Linear Graph Convolutional Networks. CoRR Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	A*	`conf`	Efficient Equivariant Network. NeurIPS Lingshen He, Yuxuan Chen, Zhengyang Shen, Yiming Dong, Yisen Wang, Zhouchen Lin
2021	A*	`conf`	Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. NeurIPS Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma
2021	J	`jnl`	Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. CoRR Hanxun Huang, Yisen Wang, Sarah Monazam Erfani, Quanquan Gu, James Bailey, Xingjun Ma
2021	A*	`conf`	Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks. NeurIPS Chen Ma, Xiangyu Guo, Li Chen, Jun-Hai Yong, Yisen Wang
2021	J	`jnl`	Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks. CoRR Chen Ma, Xiangyu Guo, Li Chen, Jun-Hai Yong, Yisen Wang
2021	J	`jnl`	Fooling Adversarial Training with Inducing Noise. CoRR Zhirui Wang, Yifei Wang, Yisen Wang
2021	A*	`conf`	GBHT: Gradient Boosting Histogram Transform for Density Estimation. ICML Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	GBHT: Gradient Boosting Histogram Transform for Density Estimation. CoRR Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	Game-theoretic Understanding of Adversarially Learned Features. CoRR Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang
2021	A*	`conf`	Gauge Equivariant Transformer. NeurIPS Lingshen He, Yiming Dong, Yisen Wang, Dacheng Tao, Zhouchen Lin
2021	J	`jnl`	Generalization in Deep RL for TSP Problems via Equivariance and Local Search. CoRR Wenbin Ouyang, Yisen Wang, Paul Weng, Shaochen Han
2021	A*	`conf`	Improving Adversarial Robustness via Channel-wise Activation Suppressing. ICLR Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang
2021	J	`jnl`	Improving Adversarial Robustness via Channel-wise Activation Suppressing. CoRR Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang
2021	—	`conf`	Improving Generalization of Deep Reinforcement Learning-based TSP Solvers. SSCI Wenbin Ouyang, Yisen Wang, Shaochen Han, Zhejian Jin, Paul Weng
2021	J	`jnl`	Improving Generalization of Deep Reinforcement Learning-based TSP Solvers. CoRR Wenbin Ouyang, Yisen Wang, Shaochen Han, Zhejian Jin, Paul Weng
2021	A*	`conf`	Leveraged Weighted Loss for Partial Label Learning. ICML Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	Leveraged Weighted Loss for Partial Label Learning. CoRR Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	Moiré Attack (MA): A New Potential Risk of Screen Photos. CoRR Dantong Niu, Ruohao Guo, Yisen Wang
2021	A*	`conf`	Morié Attack (MA): A New Potential Risk of Screen Photos. NeurIPS Dantong Niu, Ruohao Guo, Yisen Wang
2021	A*	`conf`	On Training Implicit Models. NeurIPS Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	On Training Implicit Models. CoRR Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	On the Convergence and Robustness of Adversarial Training. CoRR Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
2021	J	`jnl`	Optimization Induced Equilibrium Networks. CoRR Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Yisen Wang, Guangcan Liu, Zhouchen Lin
2021	—	`conf`	Reparameterized Sampling for Generative Adversarial Networks. ECML/PKDD (3) Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	J	`jnl`	Reparameterized Sampling for Generative Adversarial Networks. CoRR Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	A*	`conf`	Residual Relaxation for Multi-view Representation Learning. NeurIPS Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	J	`jnl`	Residual Relaxation for Multi-view Representation Learning. CoRR Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin
2021	A*	`conf`	Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness. NeurIPS Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
2021	A*	`conf`	Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. NeurIPS Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. CoRR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
2021	J	`jnl`	Understanding adversarial attacks on deep learning based medical image analysis systems. Pattern Recognit. Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu
2021	A*	`conf`	Unlearnable Examples: Making Personal Data Unexploitable. ICLR Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang
2021	J	`jnl`	Unlearnable Examples: Making Personal Data Unexploitable. CoRR Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang
2021	J	`jnl`	What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space. CoRR Shihao Zhao, Xingjun Ma, Yisen Wang, James Bailey, Bo Li, Yu-Gang Jiang
2020	J	`jnl`	A Unified Approach to Interpreting and Boosting Adversarial Transferability. CoRR Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
2020	A*	`conf`	Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles. CVPR Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, A. K. Qin, Yun Yang
2020	J	`jnl`	Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles. CoRR Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, A. K. Qin, Yun Yang
2020	A*	`conf`	Adversarial Weight Perturbation Helps Robust Generalization. NeurIPS Dongxian Wu, Shu-Tao Xia, Yisen Wang
2020	A*	`conf`	Improving Adversarial Robustness Requires Revisiting Misclassified Examples. ICLR Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu
2020	B	`conf`	Improving Gravitational Wave Detection with 2D Convolutional Neural Networks. ICPR Siyu Fan, Yisen Wang, Yuan Luo, Alexander Schmitt, Shenghua Yu
2020	—	`conf`	Improving Query Efficiency of Black-Box Adversarial Attack. ECCV (25) Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo
2020	J	`jnl`	Improving Query Efficiency of Black-box Adversarial Attack. CoRR Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo
2020	A*	`conf`	Normalized Loss Functions for Deep Learning with Noisy Labels. ICML Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey
2020	J	`jnl`	Normalized Loss Functions for Deep Learning with Noisy Labels. CoRR Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey
2020	J	`jnl`	Revisiting Loss Landscape for Adversarial Robustness. CoRR Dongxian Wu, Yisen Wang, Shutao Xia
2020	A*	`conf`	Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. ICLR Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma
2020	J	`jnl`	Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. CoRR Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma
2020	B	`conf`	Temporal Calibrated Regularization for Robust Noisy Label Learning. IJCNN Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shu-Tao Xia
2020	J	`jnl`	Temporal Calibrated Regularization for Robust Noisy Label Learning. CoRR Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shutao Xia
2019	J	`jnl`	Collaborative Representation Cascade for Single-Image Super-Resolution. IEEE Trans. Syst. Man Cybern. Syst. Yongbing Zhang, Yulun Zhang, Jian Zhang, Dong Xu, Yun Fu, Yisen Wang, Xiangyang Ji, Qionghai Dai
2019	—	`conf`	Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation. EMNLP/IJCNLP (1) Min Zeng, Yisen Wang, Yuan Luo
2019	A*	`conf`	Hilbert-Based Generative Defense for Adversarial Examples. ICCV Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shutao Xia, Yong Jiang
2019	J	`jnl`	Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation. CoRR Dongdong Chen, Yisen Wang, Jinfeng Yi, Zaiyi Chen, Zhi-Hua Zhou
2019	A*	`conf`	On the Convergence and Robustness of Adversarial Training. ICML Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
2019	A	`conf`	Self-Attentive Networks for one-shot Image Recognition. ICME Pin Fang, Yisen Wang, Yuan Luo
2019	A*	`conf`	Symmetric Cross Entropy for Robust Learning With Noisy Labels. ICCV Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
2019	J	`jnl`	Symmetric Cross Entropy for Robust Learning with Noisy Labels. CoRR Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
2019	J	`jnl`	Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems. CoRR Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu
2018	J	`jnl`	A Novel Consistent Random Forest Framework: Bernoulli Random Forests. IEEE Trans. Neural Networks Learn. Syst. Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu
2018	—	`conf`	Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. ICLR Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey
2018	J	`jnl`	Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. CoRR Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Michael E. Houle, Grant Schoenebeck, Dawn Song, James Bailey
2018	A*	`conf`	Decoupled Networks. CVPR Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song
2018	J	`jnl`	Decoupled Networks. CoRR Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song
2018	A*	`conf`	Dimensionality-Driven Learning with Noisy Labels. ICML Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi N. R. Wijewickrema, James Bailey
2018	J	`jnl`	Dimensionality-Driven Learning with Noisy Labels. CoRR Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi N. R. Wijewickrema, James Bailey
2018	A*	`conf`	Iterative Learning With Open-Set Noisy Labels. CVPR Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia
2018	J	`jnl`	Iterative Learning with Open-set Noisy Labels. CoRR Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia
2018	A	`conf`	Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. UAI Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha
2018	J	`jnl`	Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. CoRR Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha
2017	J	`jnl`	A generic denoising framework via guided principal component analysis. J. Vis. Commun. Image Represent. Tao Dai, Zhiya Xu, Haoyi Liang, Ke Gu, Qingtao Tang, Yisen Wang, Weizhi Lu, Shu-Tao Xia
2017	J	`jnl`	A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification. Knowl. Based Syst. Yisen Wang, Shu-Tao Xia, Jia Wu
2017	J	`jnl`	Link sign prediction by Variational Bayesian Probabilistic Matrix Factorization with Student-t Prior. Inf. Sci. Yisen Wang, Fangbing Liu, Shu-Tao Xia, Jia Wu
2017	J	`jnl`	Residual Convolutional CTC Networks for Automatic Speech Recognition. CoRR Yisen Wang, Xuejiao Deng, Songbai Pu, Zhiheng Huang
2017	A*	`conf`	Robust Survey Aggregation with Student-t Distribution and Sparse Representation. IJCAI Qingtao Tang, Tao Dai, Li Niu, Yisen Wang, Shu-Tao Xia, Jianfei Cai
2017	A*	`conf`	Student-t Process Regression with Student-t Likelihood. IJCAI Qingtao Tang, Li Niu, Yisen Wang, Tao Dai, Wangpeng An, Jianfei Cai, Shu-Tao Xia
2017	A*	`conf`	Unbiased Multivariate Correlation Analysis. AAAI Yisen Wang, Simone Romano, Vinh Nguyen, James Bailey, Xingjun Ma, Shu-Tao Xia
2017	Misc	`conf`	Unifying attribute splitting criteria of decision trees by Tsallis entropy. ICASSP Yisen Wang, Shu-Tao Xia
2016	B	`conf`	A novel feature subspace selection method in random forests for high dimensional data. IJCNN Yisen Wang, Shu-Tao Xia
2016	A*	`conf`	Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness. IJCAI Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu
2016	J	`jnl`	End-to-end coding for TCP. IEEE Netw. Yong Cui, Lian Wang, Xin Wang, Yisen Wang, Fengyuan Ren, Shu-Tao Xia
2016	B	`conf`	Improving decision trees by Tsallis Entropy Information Metric method. IJCNN Yisen Wang, Chao-Bing Song, Shu-Tao Xia
2016	A	`conf`	Student-t Process Regression with Dependent Student-t Noise. ECAI Qingtao Tang, Yisen Wang, Shu-Tao Xia
2015	J	`jnl`	Improving Decision Trees Using Tsallis Entropy. CoRR Yisen Wang, Chao-Bing Song, Shu-Tao Xia