Zhouchen Lin

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 295

Top Venues

CoRR

IEEE Trans. Image Process.

IEEE Trans. Pattern Anal. Mach. Intell.

NeurIPS

Publications

Xiaoqin Zhang, Jingjing Zheng, Li Zhao, Zhengyuan Zhou, Zhouchen Lin
Tensor Recovery With Weighted Tensor Average Rank. IEEE Trans. Neural Networks Learn. Syst. 35 (1) (2024)
Huan Li, Zhouchen Lin
Norm: Better Dependence on the Dimension. CoRR (2024)
Haixin Wang, Jianlong Chang, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian
LION: Implicit Vision Prompt Tuning. CoRR (2023)
Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. ICLR (2023)
Yibo Yang, Zhengyang Shen, Huan Li, Zhouchen Lin
Optimization-inspired manual architecture design and neural architecture search. Sci. China Inf. Sci. 66 (11) (2023)
Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Guangcan Liu, Zhouchen Lin
Optimization Induced Equilibrium Networks: An Explicit Optimization Perspective for Understanding Equilibrium Models. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Xiangtai Li, Shilin Xu, Yibo Yang, Haobo Yuan, Guangliang Cheng, Yunhai Tong, Zhouchen Lin, Dacheng Tao
PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation. CoRR (2023)
Bruce X. B. Yu, Jianlong Chang, Haixin Wang, Lingbo Liu, Shijie Wang, Zhiyu Wang, Junfan Lin, Lingxi Xie, Haojie Li, Zhouchen Lin, Qi Tian, Chang Wen Chen
Visual Tuning. CoRR (2023)
Yi Wu, Yanyang Xu, Wenhao Zhu, Guojie Song, Zhouchen Lin, Liang Wang, Shaoguo Liu
KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach. IJCAI (2023)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131 (1) (2023)
Long Yang, Zhixiong Huang, Fenghao Lei, Yucun Zhong, Yiming Yang, Cong Fang, Shiting Wen, Binbin Zhou, Zhouchen Lin
Policy Representation via Diffusion Probability Model for Reinforcement Learning. CoRR (2023)
Zongpeng Zhang, Zenan Ling, Tong Lin, Zhouchen Lin
Gradient Descent Optimizes Normalization-Free ResNets. IJCNN (2023)
Pengyun Yue, Hanzhen Zhao, Cong Fang, Di He, Liwei Wang, Zhouchen Lin, Song-chun Zhu
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity. CoRR (2023)
Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. NeurIPS (2023)
Pengyun Yue, Cong Fang, Zhouchen Lin
On the Lower Bound of Minimizing Polyak-Łojasiewicz functions. COLT (2023)
Yuxuan Du, Yibo Yang, Tongliang Liu, Zhouchen Lin, Bernard Ghanem, Dacheng Tao
ShadowNet for Data-Centric Quantum System Learning. CoRR (2023)
Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks. CoRR (2023)
Jianghui Wang, Cheng Yang, Xingyu Xie, Cong Fang, Zhouchen Lin
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. CoRR (2023)
Lingshen He, Yuxuan Chen, Zhengyang Shen, Yibo Yang, Zhouchen Lin
Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks. ICLR (2023)
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
SPIDE: A purely spike-based method for training feedback spiking neural networks. Neural Networks 161 (2023)
Huan Li, Zhouchen Lin
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the in the O(epsilon^(-7/4)) Complexity. J. Mach. Learn. Res. 24 (2023)
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks. CoRR (2023)
Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang
Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium. CoRR (2023)
Haotong Yang, Fanxu Meng, Zhouchen Lin, Muhan Zhang
Explaining the Complex Task Reasoning of Large Language Models with Template-Content Structure. CoRR (2023)
Pengyun Yue, Long Yang, Cong Fang, Zhouchen Lin
Zeroth-order Optimization with Weak Dimension Dependency. COLT (2023)
Yibo Yang, Haobo Yuan, Xiangtai Li, Jianlong Wu, Lefei Zhang, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao, Bernard Ghanem
Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants. CoRR (2023)
Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. CoRR (2023)
Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks. ICCV (2023)
Jianghui Wang, Yang Chen, Xingyu Xie, Cong Fang, Zhouchen Lin
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. NeurIPS (2023)
Xiaoqin Zhang, Jingjing Zheng, Di Wang, Guiying Tang, Zhengyuan Zhou, Zhouchen Lin
Structured Sparsity Optimization With Non-Convex Surrogates of $\ell _{2,0}$ℓ2,0-Norm: A Unified Algorithmic Framework. IEEE Trans. Pattern Anal. Mach. Intell. 45 (5) (2023)
Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning. CoRR (2023)
Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip H. S. Torr, Dacheng Tao
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning. ICLR (2023)
Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. CoRR (2023)
Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States. ICLR (2023)
Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu, Zhouchen Lin
A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization. NeurIPS (2023)
Mingjie Li, Yisen Wang, Zhouchen Lin
GEQ: Gaussian Kernel Inspired Equilibrium Models. NeurIPS (2023)
Qi Chen, Yifei Wang, Zhengyang Geng, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Equilibrium Image Denoising With Implicit Differentiation. IEEE Trans. Image Process. 32 (2023)
Yi Hu, Haotong Yang, Zhouchen Lin, Muhan Zhang
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models. CoRR (2023)
Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin
Global Convergence of Over-parameterized Deep Equilibrium Models. AISTATS (2023)
Huan Li, Zhouchen Lin
) Complexity. ICML (2022)
Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin
CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters. ICML (2022)
Mingjie Li, Hao Kong, Zhouchen Lin
SymNMF-Net for The Symmetric NMF Problem. CoRR (2022)
Xingyu Xie, Pan Zhou, Huan Li, Zhouchen Lin, Shuicheng Yan
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models. CoRR (2022)
Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Optimization-Induced Graph Implicit Nonlinear Diffusion. CoRR (2022)
Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR (2022)
Yibo Yang, Liang Xie, Shixiang Chen, Xiangtai Li, Zhouchen Lin, Dacheng Tao
Do We Really Need a Learnable Classifier at the End of Deep Neural Network? CoRR (2022)
Shiping Wang, Zhaoliang Chen, Shide Du, Zhouchen Lin
Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
Online Training Through Time for Spiking Neural Networks. CoRR (2022)
Haotong Yang, Zhouchen Lin, Muhan Zhang
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. CoRR (2022)
Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. ICLR (2022)
Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, Zhouchen Lin, Dacheng Tao
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? NeurIPS (2022)
Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. CoRR (2022)
Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, Zhouchen Lin
Investigating Bi-Level Optimization for Learning and Vision From a Unified Perspective: A Survey and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Jia Li, Mingqing Xiao, Cong Fang, Yue Dai, Chao Xu, Zhouchen Lin
Training Neural Networks by Lifted Proximal Operator Machines. IEEE Trans. Pattern Anal. Mach. Intell. 44 (6) (2022)
Pan Zhou, Xiao-Tong Yuan, Zhouchen Lin, Steven C. H. Hoi
A Hybrid Stochastic-Deterministic Minibatch Proximal Gradient Method for Efficient Optimization and Generalization. IEEE Trans. Pattern Anal. Mach. Intell. 44 (10) (2022)
Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CoRR (2022)
Haotong Yang, Zhouchen Lin, Muhan Zhang
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. NeurIPS (2022)
Mingjie Li, Yisen Wang, Xingyu Xie, Zhouchen Lin
Optimization inspired Multi-Branch Equilibrium Models. ICLR (2022)
Huan Li, Zhouchen Lin
) Complexity. CoRR (2022)
Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin
Global Convergence of Over-parameterized Deep Equilibrium Models. CoRR (2022)
Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. CoRR (2022)
Qi Chen, Yifei Wang, Yisen Wang, Jianlong Chang, Qi Tian, Jiansheng Yang, Zhouchen Lin
Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium. Big Data (2022)
Mingjie Li, Yisen Wang, Zhouchen Lin
CerDEQ: Certifiable Deep Equilibrium Model. ICML (2022)
Huan Li, Zhouchen Lin, Yongchun Fang
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization. J. Mach. Learn. Res. 23 (2022)
Yuanyuan Liu, Fanhua Shang, Weixin An, Hongying Liu, Zhouchen Lin
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots. ICML (2022)
Qingyan Meng, Shen Yan, Mingqing Xiao, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
Training much deeper spiking neural networks with a small number of time-steps. Neural Networks 153 (2022)
Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma, Zhouchen Lin
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs. CoRR (2022)
Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin
Towards Theoretically Inspired Neural Initialization Optimization. NeurIPS (2022)
Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. ICLR (2022)
Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CVPR (2022)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
Invertible Rescaling Network and Its Extensions. CoRR (2022)
Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma, Zhouchen Lin
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs. ICML (2022)
Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin
Under-bagging Nearest Neighbors for Imbalanced Classification. J. Mach. Learn. Res. 23 (2022)
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
Online Training Through Time for Spiking Neural Networks. NeurIPS (2022)
Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Optimization-Induced Graph Implicit Nonlinear Diffusion. ICML (2022)
Nan Ke, Tong Lin, Zhouchen Lin, Xiao-Hua Zhou, Taoyun Ji
Convolutional Transformer Networks for Epileptic Seizure Detection. CIKM (2022)
Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin
Towards Theoretically Inspired Neural Initialization Optimization. CoRR (2022)
Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin
Leveraged Weighted Loss for Partial Label Learning. CoRR (2021)
Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen
Histogram Transform Ensembles for Large-scale Regression. J. Mach. Learn. Res. 22 (2021)
Yuanyuan Liu, Fanhua Shang, Hongying Liu, Lin Kong, Licheng Jiao, Zhouchen Lin
Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43 (12) (2021)
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. NeurIPS (2021)
Xiangtai Li, Hao He, Xia Li, Duo Li, Guangliang Cheng, Jianping Shi, Lubin Weng, Yunhai Tong, Zhouchen Lin
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation. CoRR (2021)
Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. CoRR (2021)
Ke Sun, Mingjie Li, Zhouchen Lin
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness. CoRR (2021)
Hao Kong, Canyi Lu, Zhouchen Lin
Tensor Q-rank: new data dependent definition of tensor rank. Mach. Learn. 110 (7) (2021)
Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua
Graph Contrastive Clustering. CoRR (2021)
Qigong Sun, Xiufang Li, Fanhua Shang, Hongying Liu, Kang Yang, Licheng Jiao, Zhouchen Lin
Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration. CoRR (2021)
Xinbang Zhang, Jianlong Chang, Yiwen Guo, Gaofeng Meng, Shiming Xiang, Zhouchen Lin, Chunhong Pan
DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling. IEEE Trans. Pattern Anal. Mach. Intell. 43 (9) (2021)
Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs. AAAI (2021)
Yong Chen, Yuqing Hou, Shu Leng, Qing Zhang, Zhouchen Lin, Dell Zhang
Long-Tail Hashing. SIGIR (2021)
Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Residual Relaxation for Multi-view Representation Learning. NeurIPS (2021)
Ke Sun, Zhanxing Zhu, Zhouchen Lin
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. ICLR (2021)
Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Residual Relaxation for Multi-view Representation Learning. CoRR (2021)
Huan Li, Zhouchen Lin
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization. CoRR (2021)
Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. NeurIPS (2021)
Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search. CoRR (2021)
Tiancheng Shen, Yibo Yang, Zhouchen Lin, Mingbin Zhang
Recurrent learning with clique structures for prostate sparse-view CT artifacts reduction. IET Image Process. 15 (3) (2021)
Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
GBHT: Gradient Boosting Histogram Transform for Density Estimation. CoRR (2021)
Xiangtai Li, Xia Li, Ansheng You, Li Zhang, Guangliang Cheng, Kuiyuan Yang, Yunhai Tong, Zhouchen Lin
Towards Efficient Scene Understanding via Squeeze Reasoning. IEEE Trans. Image Process. 30 (2021)
Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua
Graph Contrastive Clustering. ICCV (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Zhouchen Lin