


default search action
Zhouchen Lin
Person information
- affiliation (PhD 2000): Peking University, Department of Machine Intelligence, Beijing, China
- affiliation (former): Microsoft Research Asia, Beijing, China
Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
- [e18]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15031, Springer 2025, ISBN 978-981-97-8486-8 [contents] - [e17]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part II. Lecture Notes in Computer Science 15032, Springer 2025, ISBN 978-981-97-8489-9 [contents] - [e16]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part III. Lecture Notes in Computer Science 15033, Springer 2025, ISBN 978-981-97-8501-8 [contents] - [e15]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024 Urumqi, China, October 18-20, 2024 Proceedings, Part IV. Lecture Notes in Computer Science 15034, Springer 2025, ISBN 978-981-97-8504-9 [contents] - [e14]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part V. Lecture Notes in Computer Science 15035, Springer 2025, ISBN 978-981-97-8619-0 [contents] - [e13]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 15036, Springer 2025, ISBN 978-981-97-8507-0 [contents] - [e12]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part VII. Lecture Notes in Computer Science 15037, Springer 2025, ISBN 978-981-97-8510-0 [contents] - [e11]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part VIII. Lecture Notes in Computer Science 15038, Springer 2025, ISBN 978-981-97-8684-8 [contents] - [e10]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part IX. Lecture Notes in Computer Science 15039, Springer 2025, ISBN 978-981-97-8691-6 [contents] - [e9]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu
:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part X. Lecture Notes in Computer Science 15040, Springer 2025, ISBN 978-981-97-8791-3 [contents] - [e8]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part XI. Lecture Notes in Computer Science 15041, Springer 2025, ISBN 978-981-97-8794-4 [contents] - [e7]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part XII. Lecture Notes in Computer Science 15042, Springer 2025, ISBN 978-981-97-8857-6 [contents] - [e6]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part XIII. Lecture Notes in Computer Science 15043, Springer 2025, ISBN 978-981-97-8492-9 [contents] - [e5]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part XIV. Lecture Notes in Computer Science 15044, Springer 2025, ISBN 978-981-97-8495-0 [contents] - [e4]Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu:
Pattern Recognition and Computer Vision - 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18-20, 2024, Proceedings, Part XV. Lecture Notes in Computer Science 15045, Springer 2025, ISBN 978-981-97-8498-1 [contents] - 2024
- [j134]Zongpeng Zhang
, Taoyun Ji, Mingqing Xiao
, Wen Wang, Guojing Yu, Tong Lin
, Yuwu Jiang, Xiaohua Zhou, Zhouchen Lin:
Cross-patient automatic epileptic seizure detection using patient-adversarial neural networks with spatio-temporal EEG augmentation. Biomed. Signal Process. Control. 89: 105664 (2024) - [j133]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. ACM Comput. Surv. 56(12): 297:1-297:38 (2024) - [j132]Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan:
Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training. J. Mach. Learn. Res. 25: 83:1-83:74 (2024) - [j131]Shen Yan
, Qingyan Meng
, Mingqing Xiao
, Yisen Wang
, Zhouchen Lin
:
Sampling complex topology structures for spiking neural networks. Neural Networks 172: 106121 (2024) - [j130]Zhengyang Shen, Yeqing Qiu
, Jialun Liu, Lingshen He, Zhouchen Lin
:
Efficient learning of Scale-Adaptive Nearly Affine Invariant Networks. Neural Networks 174: 106229 (2024) - [j129]Zhoutong Wu
, Mingqing Xiao
, Cong Fang
, Zhouchen Lin
:
Designing Universally-Approximating Deep Neural Networks: A First-Order Optimization Approach. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 6231-6246 (2024) - [j128]Pan Zhou
, Xingyu Xie
, Zhouchen Lin
, Shuicheng Yan
:
Towards Understanding Convergence and Generalization of AdamW. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 6486-6493 (2024) - [j127]Xingyu Xie
, Pan Zhou
, Huan Li
, Zhouchen Lin
, Shuicheng Yan
:
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 9508-9520 (2024) - [j126]Xiangtai Li
, Shilin Xu
, Yibo Yang
, Haobo Yuan
, Guangliang Cheng
, Yunhai Tong
, Zhouchen Lin
, Ming-Hsuan Yang
, Dacheng Tao
:
Panoptic-PartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11087-11103 (2024) - [j125]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): 1142-1156 (2024) - [c158]Haixin Wang, Jianlong Chang, Yihang Zhai, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian:
LION: Implicit Vision Prompt Tuning. AAAI 2024: 5372-5380 - [c157]Yikang Li, Yeqing Qiu, Yuxuan Chen, Lingshen He, Zhouchen Lin:
Affine Equivariant Networks Based on Differential Invariants. CVPR 2024: 5546-5556 - [c156]Xin Xu, Zhouchen Lin:
MixCon: A Hybrid Architecture for Efficient and Adaptive Sequence Modeling. ECAI 2024: 1027-1034 - [c155]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. ICLR 2024 - [c154]Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin:
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. ICML 2024 - [c153]Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu:
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective. ICML 2024 - [c152]Zhoutong Wu, Yimu Zhang, Cong Fang, Zhouchen Lin:
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics. NeurIPS 2024 - [c151]Yiming Dong, Zhouchen Lin:
Reducing Memory Footprint in Deep Network Training by Gradient Space Reutilization. PRCV (2) 2024: 376-390 - [i137]Huan Li, Zhouchen Lin:
On the O(×d/T1/4) Convergence Rate of RMSProp and Its Momentum Extension Measured by 𝓁l Norm: Better Dependence on the Dimension. CoRR abs/2402.00389 (2024) - [i136]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. CoRR abs/2402.11984 (2024) - [i135]Yang Chen, Yitao Liang, Zhouchen Lin:
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery. CoRR abs/2402.18910 (2024) - [i134]Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin:
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. CoRR abs/2405.16851 (2024) - [i133]Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu:
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective. CoRR abs/2406.11249 (2024) - [i132]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks. CoRR abs/2407.12516 (2024) - [i131]Lexiang Hu, Yisen Wang, Zhouchen Lin:
EKAN: Equivariant Kolmogorov-Arnold Networks. CoRR abs/2410.00435 (2024) - [i130]Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, Zhouchen Lin:
Pyramidal Flow Matching for Efficient Video Generative Modeling. CoRR abs/2410.05954 (2024) - [i129]Yang Chen, Yitao Liang, Zhouchen Lin:
Low-Dimension-to-High-Dimension Generalization And Its Implications for Length Generalization. CoRR abs/2410.08898 (2024) - [i128]Yisen Wang, Yichuan Mo, Dongxian Wu, Mingjie Li, Xingjun Ma, Zhouchen Lin:
On the Adversarial Transferability of Generalized "Skip Connections". CoRR abs/2410.08950 (2024) - [i127]Lexiang Hu, Yikang Li, Zhouchen Lin:
Symmetry Discovery for Different Data Types. CoRR abs/2410.09841 (2024) - [i126]Haotong Yang, Yi Hu, Shijia Kang, Zhouchen Lin, Muhan Zhang:
Number Cookbook: Number Understanding of Language Models and How to Improve It. CoRR abs/2411.03766 (2024) - [i125]Yiming Dong, Huan Li, Zhouchen Lin:
Convergence Rate Analysis of LION. CoRR abs/2411.07724 (2024) - [i124]Haotong Yang, Xiyuan Wang, Qian Tao, Shuxian Hu, Zhouchen Lin, Muhan Zhang:
GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model. CoRR abs/2412.06849 (2024) - [i123]Shihao Shao, Yikang Li, Zhouchen Lin, Qinghua Cui:
High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces. CoRR abs/2412.18263 (2024) - 2023
- [j124]Yibo Yang, Zhengyang Shen, Huan Li, Zhouchen Lin:
Optimization-inspired manual architecture design and neural architecture search. Sci. China Inf. Sci. 66(11) (2023) - [j123]Mingqing Xiao
, Shuxin Zheng, Chang Liu
, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131(1): 134-159 (2023) - [j122]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: 157:1-157:37 (2023) - [j121]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: 9-24 (2023) - [j120]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): 3604-3616 (2023) - [j119]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): 6386-6402 (2023) - [j118]Qi Chen
, Yifei Wang
, Zhengyang Geng
, Yisen Wang, Jiansheng Yang, Zhouchen Lin
:
Equilibrium Image Denoising With Implicit Differentiation. IEEE Trans. Image Process. 32: 1868-1881 (2023) - [c150]Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu:
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. ACML 2023: 1276-1291 - [c149]Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin:
Global Convergence of Over-parameterized Deep Equilibrium Models. AISTATS 2023: 767-787 - [c148]Pengyun Yue, Cong Fang, Zhouchen Lin:
On the Lower Bound of Minimizing Polyak-Łojasiewicz functions. COLT 2023: 2948-2968 - [c147]Pengyun Yue, Long Yang, Cong Fang, Zhouchen Lin:
Zeroth-order Optimization with Weak Dimension Dependency. COLT 2023: 4429-4472 - [c146]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: 6143-6153 - [c145]Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. ICLR 2023 - [c144]Lingshen He, Yuxuan Chen, Zhengyang Shen, Yibo Yang, Zhouchen Lin:
Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks. ICLR 2023 - [c143]Mingjie Li
, Yifei Wang, Yisen Wang, Zhouchen Lin:
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States. ICLR 2023 - [c142]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 - [c141]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: 2370-2378 - [c140]Zongpeng Zhang, Zenan Ling, Tong Lin, Zhouchen Lin:
Gradient Descent Optimizes Normalization-Free ResNets. IJCNN 2023: 1-8 - [c139]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 - [c138]Mingjie Li, Yisen Wang, Zhouchen Lin:
GEQ: Gaussian Kernel Inspired Equilibrium Models. NeurIPS 2023 - [c137]Jianghui Wang, Yang Chen, Xingyu Xie, Cong Fang, Zhouchen Lin:
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. NeurIPS 2023 - [c136]Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. NeurIPS 2023 - [i122]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 abs/2301.00954 (2023) - [i121]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks. CoRR abs/2302.00232 (2023) - [i120]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 abs/2302.03004 (2023) - [i119]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 abs/2302.14311 (2023) - [i118]Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang:
Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium. CoRR abs/2303.00970 (2023) - [i117]Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
A Message Passing Perspective on Learning Dynamics of Contrastive Learning. CoRR abs/2303.04435 (2023) - [i116]Haixin Wang, Jianlong Chang, Xiao Luo
, Jinan Sun, Zhouchen Lin, Qi Tian:
LION: Implicit Vision Prompt Tuning. CoRR abs/2303.09992 (2023) - [i115]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 abs/2305.06061 (2023) - [i114]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 abs/2305.13122 (2023) - [i113]Yi Hu, Haotong Yang, Zhouchen Lin, Muhan Zhang:
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models. CoRR abs/2305.18507 (2023) - [i112]Jianghui Wang, Cheng Yang, Xingyu Xie, Cong Fang, Zhouchen Lin:
Task-Robust Pre-Training for Worst-Case Downstream Adaptation. CoRR abs/2306.12070 (2023) - [i111]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 abs/2308.01746 (2023) - [i110]Yuxuan Du, Yibo Yang, Tongliang Liu, Zhouchen Lin, Bernard Ghanem, Dacheng Tao:
ShadowNet for Data-Centric Quantum System Learning. CoRR abs/2308.11290 (2023) - [i109]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 abs/2309.13307 (2023) - [i108]Haotong Yang, Fanxu Meng, Zhouchen Lin, Muhan Zhang:
Explaining the Complex Task Reasoning of Large Language Models with Template-Content Structure. CoRR abs/2310.05452 (2023) - [i107]Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang:
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective. CoRR abs/2310.19360 (2023) - 2022
- [b2]Zhouchen Lin, Huan Li, Cong Fang:
Alternating Direction Method of Multipliers for Machine Learning. Springer 2022, ISBN 978-981-16-9839-2, pp. 1-263 - [j117]Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Under-bagging Nearest Neighbors for Imbalanced Classification. J. Mach. Learn. Res. 23: 118:1-118:63 (2022) - [j116]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: 222:1-222:41 (2022) - [j115]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: 254-268 (2022) - [j114]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): 3334-3348 (2022) - [j113]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): 5042-5055 (2022) - [j112]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): 5933-5946 (2022) - [j111]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): 10045-10067 (2022) - [c135]Qi Chen, Yifei Wang, Yisen Wang, Jianlong Chang, Qi Tian, Jiansheng Yang, Zhouchen Lin:
Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium. IEEE Big Data 2022: 864-873 - [c134]Nan Ke, Tong Lin, Zhouchen Lin, Xiao-Hua Zhou, Taoyun Ji:
Convolutional Transformer Networks for Epileptic Seizure Detection. CIKM 2022: 4109-4113 - [c133]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: 12434-12443 - [c132]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. ICLR 2022 - [c131]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 - [c130]Mingjie Li
, Yisen Wang, Xingyu Xie, Zhouchen Lin:
Optimization inspired Multi-Branch Equilibrium Models. ICLR 2022 - [c129]Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Optimization-Induced Graph Implicit Nonlinear Diffusion. ICML 2022: 3648-3661 - [c128]Mingjie Li
, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin:
G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters. ICML 2022: 12782-12796 - [c127]Huan Li, Zhouchen Lin:
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε-7/4) Complexity. ICML 2022: 12901-12916 - [c126]Mingjie Li
, Yisen Wang, Zhouchen Lin:
CerDEQ: Certifiable Deep Equilibrium Model. ICML 2022: 12998-13013 - [c125]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: 14008-14035 - [c124]Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma, Zhouchen Lin:
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs. ICML 2022: 19827-19846 - [c123]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Online Training Through Time for Spiking Neural Networks. NeurIPS 2022 - [c122]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 - [c121]Haotong Yang, Zhouchen Lin, Muhan Zhang:
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. NeurIPS 2022 - [c120]Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin:
Towards Theoretically Inspired Neural Initialization Optimization. NeurIPS 2022