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ORCIDZhouchen Lin
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- affiliation (PhD 2000): Peking University, Department of Machine Intelligence, Beijing, China
- affiliation (former): Microsoft Research Asia, Beijing, China
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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) - [c157]Haixin Wang, Jianlong Chang, Yihang Zhai, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian:
LION: Implicit Vision Prompt Tuning. AAAI 2024: 5372-5380 - [c156]Yikang Li, Yeqing Qiu, Yuxuan Chen, Lingshen He, Zhouchen Lin:
Affine Equivariant Networks Based on Differential Invariants. CVPR 2024: 5546-5556 - [c155]Xin Xu, Zhouchen Lin:
MixCon: A Hybrid Architecture for Efficient and Adaptive Sequence Modeling. ECAI 2024: 1027-1034 - [c154]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. ICLR 2024 - [c153]Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin:
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. ICML 2024 - [c152]Yang Chen, Cong Fang, Zhouchen Lin, Bing Liu:
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective. ICML 2024 - [c151]Yiming Dong, Zhouchen Lin:
Reducing Memory Footprint in Deep Network Training by Gradient Space Reutilization. PRCV (2) 2024: 376-390 - [i133]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) - [i132]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) - [i131]Yang Chen, Yitao Liang, Zhouchen Lin:
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery. CoRR abs/2402.18910 (2024) - [i130]Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin:
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. CoRR abs/2405.16851 (2024) - [i129]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) - [i128]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) - [i127]Lexiang Hu, Yisen Wang, Zhouchen Lin:
EKAN: Equivariant Kolmogorov-Arnold Networks. CoRR abs/2410.00435 (2024) - [i126]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) - [i125]Yang Chen, Yitao Liang, Zhouchen Lin:
Low-Dimension-to-High-Dimension Generalization And Its Implications for Length Generalization. CoRR abs/2410.08898 (2024) - [i124]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) - [i123]Lexiang Hu, Yikang Li, Zhouchen Lin:
Symmetry Discovery for Different Data Types. CoRR abs/2410.09841 (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 - [i106]Huan Li, Zhouchen Lin:
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε-7/4) Complexity. CoRR abs/2201.11411 (2022) - [i105]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 abs/2203.09081 (2022) - [i104]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. CoRR abs/2203.13455 (2022) - [i103]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 abs/2203.13457 (2022) - [i102]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 abs/2205.00459 (2022) - [i101]Mingjie Li, Hao Kong, Zhouchen Lin:
SymNMF-Net for The Symmetric NMF Problem. CoRR abs/2205.13214 (2022) - [i100]Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin:
Global Convergence of Over-parameterized Deep Equilibrium Models. CoRR abs/2205.13814 (2022) - [i99]Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang:
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR abs/2206.09567 (2022) - [i98]Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Optimization-Induced Graph Implicit Nonlinear Diffusion. CoRR abs/2206.14418 (2022) - [i97]Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma, Zhouchen Lin:
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs. CoRR abs/2208.03720 (2022) - [i96]Xingyu Xie, Pan Zhou, Huan Li, Zhouchen Lin, Shuicheng Yan:
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models. CoRR abs/2208.06677 (2022) - [i95]Haotong Yang, Zhouchen Lin, Muhan Zhang:
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. CoRR abs/2209.08858 (2022) - [i94]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. CoRR abs/2210.04188 (2022) - [i93]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin:
Online Training Through Time for Spiking Neural Networks. CoRR abs/2210.04195 (2022) - [i92]Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin:
Towards Theoretically Inspired Neural Initialization Optimization. CoRR abs/2210.05956 (2022) - 2021
- [j110]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): 648-655 (2021) - [j109]Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen:
Histogram Transform Ensembles for Large-scale Regression. J. Mach. Learn. Res. 22: 95:1-95:87 (2021) - [j108]Hao Kong, Canyi Lu, Zhouchen Lin:
Tensor Q-rank: new data dependent definition of tensor rank. Mach. Learn. 110(7): 1867-1900 (2021) - [j107]Pan Zhou, Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Tensor Low-Rank Representation for Data Recovery and Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 43(5): 1718-1732 (2021) - [j106]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): 2905-2920 (2021) - [j105]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): 4242-4255 (2021) - [j104]Jianlong Wu, Xingxu Xie, Liqiang Nie, Zhouchen Lin, Hongbin Zha:
Reconstruction regularized low-rank subspace learning for cross-modal retrieval. Pattern Recognit. 113: 107813 (2021) - [j103]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: 7050-7063 (2021) - [c119]Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin:
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding. AAAI 2021: 8501-8509 - [c118]Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma:
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs. AAAI 2021: 9585-9593 - [c117]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. CVPR 2021: 4217-4226 - [c116]Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin:
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search. CVPR 2021: 6667-6676 - [c115]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. ICCV 2021: 9204-9213 - [c114]Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin:
Is Attention Better Than Matrix Decomposition? ICLR 2021 - [c113]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. ICLR 2021 - [c112]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. ICML 2021: 2233-2243 - [c111]Ruili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha:
Uncertainty Principles of Encoding GANs. ICML 2021: 3240-3251 - [c110]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. ICML 2021: 11091-11100 - [c109]Nan Ke, Tong Lin, Zhouchen Lin:
Channel-Weighted Squeeze-and-Excitation Networks For Epileptic Seizure Detection. ICTAI 2021: 666-673 - [c108]Lingshen He, Yuxuan Chen, Zhengyang Shen, Yiming Dong, Yisen Wang, Zhouchen Lin:
Efficient Equivariant Network. NeurIPS 2021: 5290-5302 - [c107]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. NeurIPS 2021: 5758-5769 - [c106]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. NeurIPS 2021: 12104-12115 - [c105]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. NeurIPS 2021: 14516-14528 - [c104]Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin:
On Training Implicit Models. NeurIPS 2021: 24247-24260 - [c103]Lingshen He, Yiming Dong, Yisen Wang, Dacheng Tao, Zhouchen Lin:
Gauge Equivariant Transformer. NeurIPS 2021: 27331-27343 - [c102]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. ECML/PKDD (3) 2021: 494-509 - [c101]Yong Chen, Yuqing Hou, Shu Leng, Qing Zhang, Zhouchen Lin, Dell Zhang:
Long-Tail Hashing. SIGIR 2021: 1328-1338 - [i91]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 abs/2101.11342 (2021) - [i90]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. CoRR abs/2101.11517 (2021) - [i89]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. CoRR abs/2102.10739 (2021) - [i88]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 abs/2103.06564 (2021) - [i87]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. CoRR abs/2104.01429 (2021) - [i86]Huan Li, Zhouchen Lin:
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization. CoRR abs/2104.02596 (2021) - [i85]Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma:
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs. CoRR abs/2104.03584 (2021) - [i84]Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Yisen Wang, Guangcan Liu, Zhouchen Lin:
Optimization Induced Equilibrium Networks. CoRR abs/2105.13228 (2021) - [i83]Hanyuan Hang, Tao Huang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression. CoRR abs/2106.01986 (2021) - [i82]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. CoRR abs/2106.05731 (2021) - [i81]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. CoRR abs/2106.05738 (2021) - [i80]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 abs/2106.09886 (2021) - [i79]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. CoRR abs/2107.00352 (2021) - [i78]Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Under-bagging Nearest Neighbors for Imbalanced Classification. CoRR abs/2109.00531 (2021) - [i77]Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin:
Is Attention Better Than Matrix Decomposition? CoRR abs/2109.04553 (2021) - [i76]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. CoRR abs/2109.14247 (2021) - [i75]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. CoRR abs/2110.15348 (2021) - [i74]Ke Sun, Mingjie Li, Zhouchen Lin:
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness. CoRR abs/2111.01996 (2021) - [i73]Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin:
On Training Implicit Models. CoRR abs/2111.05177 (2021) - 2020
- [b1]Zhouchen Lin, Huan Li, Cong Fang:
Accelerated Optimization for Machine Learning - First-Order Algorithms. Springer 2020, ISBN 978-981-15-2909-2, pp. 1-275 - [j102]Huan Li, Zhouchen Lin:
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent. J. Mach. Learn. Res. 21: 33:1-33:45 (2020) - [j101]Huan Li, Zhouchen Lin:
Provable accelerated gradient method for nonconvex low rank optimization. Mach. Learn. 109(1): 103-134 (2020) - [j100]Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan:
Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm. IEEE Trans. Pattern Anal. Mach. Intell. 42(4): 925-938 (2020) - [j99]Risheng Liu, Shichao Cheng, Yi He, Xin Fan, Zhouchen Lin, Zhongxuan Luo:
On the Convergence of Learning-Based Iterative Methods for Nonconvex Inverse Problems. IEEE Trans. Pattern Anal. Mach. Intell. 42(12): 3027-3039 (2020) - [j98]Huan Li, Cong Fang, Zhouchen Lin:
Accelerated First-Order Optimization Algorithms for Machine Learning. Proc. IEEE 108(11): 2067-2082 (2020) - [j97]Huan Li, Zhouchen Lin:
Revisiting EXTRA for Smooth Distributed Optimization. SIAM J. Optim. 30(3): 1795-1821 (2020) - [j96]Yinwei Wei, Xiang Wang, Weili Guan, Liqiang Nie, Zhouchen Lin, Baoquan Chen:
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding. IEEE Trans. Image Process. 29: 1-14 (2020) - [j95]Huan Li, Cong Fang, Wotao Yin, Zhouchen Lin:
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. IEEE Trans. Signal Process. 68: 4855-4870 (2020) - [c100]Ke Sun, Zhouchen Lin, Zhanxing Zhu:
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes. AAAI 2020: 5892-5899 - [c99]Jianlong Wu, Xingyu Xie, Liqiang Nie, Zhouchen Lin, Hongbin Zha:
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering. AAAI 2020: 6388-6395 - [c98]Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li, Tiancheng Shen, Zhouchen Lin:
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families. AAAI 2020: 6648-6655 - [c97]Yueying Kao, Weiming Li, Qiang Wang, Zhouchen Lin, Wooshik Kim, Sunghoon Hong:
Synthetic Depth Transfer for Monocular 3D Object Pose Estimation in the Wild. AAAI 2020: 11221-11228 - [c96]Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin:
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation. AAAI 2020: 12637-12644 - [c95]Xia Li, Yibo Yang, Qijie Zhao, Tiancheng Shen, Zhouchen Lin, Hong Liu:
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation. CVPR 2020: 8947-8956 - [c94]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [c93]Xiangtai Li, Xia Li, Li Zhang, Guangliang Cheng, Jianping Shi, Zhouchen Lin, Shaohua Tan, Yunhai Tong:
Improving Semantic Segmentation via Decoupled Body and Edge Supervision. ECCV (17) 2020: 435-452 - [c92]Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin:
Boosted Histogram Transform for Regression. ICML 2020: 1251-1261 - [c91]Mingjie Li, Lingshen He, Zhouchen Lin:
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability. ICML 2020: 5874-5883 - [c90]Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma:
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions. ICML 2020: 8697-8706 - [c89]Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin:
Maximum-and-Concatenation Networks. ICML 2020: 10483-10494 - [c88]Yibo Yang, Hongyang Li, Shan You, Fei Wang, Chen Qian, Zhouchen Lin:
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding. NeurIPS 2020 - [i72]Huan Li, Zhouchen Lin:
Revisiting EXTRA for Smooth Distributed Optimization. CoRR abs/2002.10110 (2020) - [i71]Xia Li, Yibo Yang, Qijie Zhao, Tiancheng Shen, Zhouchen Lin, Hong Liu:
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation. CoRR abs/2003.10211 (2020) - [i70]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i69]Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu:
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data. CoRR abs/2006.07841 (2020) - [i68]Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin:
Maximum-and-Concatenation Networks. CoRR abs/2007.04630 (2020) - [i67]Xiangtai Li, Xia Li, Li Zhang, Guangliang Cheng, Jianping Shi, Zhouchen Lin, Shaohua Tan, Yunhai Tong:
Improving Semantic Segmentation via Decoupled Body and Edge Supervision. CoRR abs/2007.10035 (2020) - [i66]Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma:
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions. CoRR abs/2007.10408 (2020) - [i65]Huan Li, Zhouchen Lin, Yongchun Fang:
Optimal Accelerated Variance Reduced EXTRA and DIGing for Strongly Convex and Smooth Decentralized Optimization. CoRR abs/2009.04373 (2020) - [i64]Yibo Yang, Hongyang Li, Shan You, Fei Wang, Chen Qian, Zhouchen Lin:
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding. CoRR abs/2010.06176 (2020) - [i63]Xiangtai Li, Xia Li, Ansheng You, Li Zhang, Guangliang Cheng, Kuiyuan Yang, Yunhai Tong, Zhouchen Lin:
Towards Efficient Scene Understanding via Squeeze Reasoning. CoRR abs/2011.03308 (2020) - [i62]Risheng Liu, Zhu Liu, Pan Mu, Zhouchen Lin, Xin Fan, Zhongxuan Luo:
Learning Optimization-inspired Image Propagation with Control Mechanisms and Architecture Augmentations for Low-level Vision. CoRR abs/2012.05435 (2020)
2010 – 2019
- 2019
- [j94]Gaopeng Jian, Zhouchen Lin, Rongquan Feng:
Two-weight and three-weight linear codes based on Weil sums. Finite Fields Their Appl. 57: 92-107 (2019) - [j93]Huan Li, Zhouchen Lin:
Accelerated Alternating Direction Method of Multipliers: An Optimal O(1 / K) Nonergodic Analysis. J. Sci. Comput. 79(2): 671-699 (2019) - [j92]Zhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao Zhang:
ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decomposition. Neural Networks 110: 104-115 (2019) - [j91]Canyi Lu, Jiashi Feng, Zhouchen Lin, Tao Mei, Shuicheng Yan:
Subspace Clustering by Block Diagonal Representation. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 487-501 (2019) - [j90]Chunyu Wang, Yizhou Wang, Zhouchen Lin, Alan L. Yuille:
Robust 3D Human Pose Estimation from Single Images or Video Sequences. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1227-1241 (2019) - [j89]Baohua Li, Huchuan Lu, Ying Zhang, Zhouchen Lin, Wei Wu:
Subspace Clustering Under Complex Noise. IEEE Trans. Circuits Syst. Video Technol. 29(4): 930-940 (2019) - [j88]Yan Zheng, Zhouchen Lin:
The Augmented Homogeneous Coordinates Matrix-Based Projective Mismatch Removal for Partial-Duplicate Image Search. IEEE Trans. Image Process. 28(1): 181-193 (2019) - [j87]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Essential Tensor Learning for Multi-View Spectral Clustering. IEEE Trans. Image Process. 28(12): 5910-5922 (2019) - [j86]Wenming Zheng, Cheng Lu, Zhouchen Lin, Tong Zhang, Zhen Cui, Wankou Yang:
ℓ1-Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions. IEEE Trans. Neural Networks Learn. Syst. 30(10): 2898-2915 (2019) - [c87]Jia Li, Cong Fang, Zhouchen Lin:
Lifted Proximal Operator Machines. AAAI 2019: 4181-4188 - [c86]Cong Fang, Zhouchen Lin, Tong Zhang:
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. COLT 2019: 1192-1234 - [c85]Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin:
Self-Supervised Convolutional Subspace Clustering Network. CVPR 2019: 5473-5482 - [c84]Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha:
Deep Comprehensive Correlation Mining for Image Clustering. ICCV 2019: 8149-8158 - [c83]Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, Hong Liu:
Expectation-Maximization Attention Networks for Semantic Segmentation. ICCV 2019: 9166-9175 - [c82]Xingyu Xie, Jianlong Wu, Guangcan Liu, Zhisheng Zhong, Zhouchen Lin:
Differentiable Linearized ADMM. ICML 2019: 6902-6911 - [c81]Tiancheng Shen, Xia Li, Zhisheng Zhong, Jianlong Wu, Zhouchen Lin:
R ^2 2 -Net: Recurrent and Recursive Network for Sparse-View CT Artifacts Removal. MICCAI (6) 2019: 319-327 - [c80]Ke Sun, Zhouchen Lin, Hantao Guo, Zhanxing Zhu:
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. PRCV (1) 2019: 431-443 - [c79]Lingshen He, Xingyu Xie, Zhouchen Lin:
Neural Ordinary Differential Equations with Envolutionary Weights. PRCV (1) 2019: 598-610 - [e3]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part I. Lecture Notes in Computer Science 11857, Springer 2019, ISBN 978-3-030-31653-2 [contents] - [e2]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part II. Lecture Notes in Computer Science 11858, Springer 2019, ISBN 978-3-030-31722-5 [contents] - [e1]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part III. Lecture Notes in Computer Science 11859, Springer 2019, ISBN 978-3-030-31725-6 [contents] - [i61]Cong Fang, Zhouchen Lin, Tong Zhang:
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. CoRR abs/1902.00247 (2019) - [i60]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors. CoRR abs/1902.11019 (2019) - [i59]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN. CoRR abs/1902.11029 (2019) - [i58]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks. CoRR abs/1902.11038 (2019) - [i57]Ke Sun, Hantao Guo, Zhanxing Zhu, Zhouchen Lin:
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. CoRR abs/1902.11045 (2019) - [i56]Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha:
Deep Comprehensive Correlation Mining for Image Clustering. CoRR abs/1904.06925 (2019) - [i55]Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin:
Self-Supervised Convolutional Subspace Clustering Network. CoRR abs/1905.00149 (2019) - [i54]Xingyu Xie, Jianlong Wu, Zhisheng Zhong, Guangcan Liu, Zhouchen Lin:
Differentiable Linearized ADMM. CoRR abs/1905.06179 (2019) - [i53]Zhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao Zhang:
ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition. CoRR abs/1906.07671 (2019) - [i52]Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, Hong Liu:
Expectation-Maximization Attention Networks for Semantic Segmentation. CoRR abs/1907.13426 (2019) - [i51]Ke Sun, Zhouchen Lin, Zhanxing Zhu:
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. CoRR abs/1908.05081 (2019) - [i50]Hao Kong, Zhouchen Lin:
Tensor Q-Rank: A New Data Dependent Tensor Rank. CoRR abs/1910.12016 (2019) - [i49]Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin:
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation. CoRR abs/1911.07527 (2019) - [i48]Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu:
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. CoRR abs/1911.09307 (2019) - [i47]Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li, Tiancheng Shen, Zhouchen Lin:
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families. CoRR abs/1911.10305 (2019) - [i46]Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen:
Histogram Transform Ensembles for Large-scale Regression. CoRR abs/1912.04738 (2019) - 2018
- [j85]Pan Zhou, Cong Fang, Zhouchen Lin, Chao Zhang, Edward Y. Chang:
Dictionary learning with structured noise. Neurocomputing 273: 414-423 (2018) - [j84]Chen-Yan Bai, Jia Li, Zhouchen Lin:
Demosaicking based on channel-correlation adaptive dictionary learning. J. Electronic Imaging 27(04): 043047 (2018) - [j83]Thierry Bouwmans, Namrata Vaswani, Paul Rodríguez, René Vidal, Zhouchen Lin:
Introduction to the Issue on Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications. IEEE J. Sel. Top. Signal Process. 12(6): 1127-1130 (2018) - [j82]Hao Kong, Xingyu Xie, Zhouchen Lin:
t-Schatten-p Norm for Low-Rank Tensor Recovery. IEEE J. Sel. Top. Signal Process. 12(6): 1405-1419 (2018) - [j81]Zhouchen Lin, Chen Xu, Hongbin Zha:
Robust Matrix Factorization by Majorization Minimization. IEEE Trans. Pattern Anal. Mach. Intell. 40(1): 208-220 (2018) - [j80]Canyi Lu, Jiashi Feng, Shuicheng Yan, Zhouchen Lin:
A Unified Alternating Direction Method of Multipliers by Majorization Minimization. IEEE Trans. Pattern Anal. Mach. Intell. 40(3): 527-541 (2018) - [j79]Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin:
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 40(9): 2066-2080 (2018) - [j78]Thierry Bouwmans, Sajid Javed, Hongyang Zhang, Zhouchen Lin, Ricardo Otazo:
On the Applications of Robust PCA in Image and Video Processing. Proc. IEEE 106(8): 1427-1457 (2018) - [j77]Canyi Lu, Huan Li, Zhouchen Lin:
Optimized projections for compressed sensing via direct mutual coherence minimization. Signal Process. 151: 45-55 (2018) - [j76]Yameng Huang, Zhouchen Lin:
Binary Multidimensional Scaling for Hashing. IEEE Trans. Image Process. 27(1): 406-418 (2018) - [j75]Pan Zhou, Canyi Lu, Zhouchen Lin, Chao Zhang:
Tensor Factorization for Low-Rank Tensor Completion. IEEE Trans. Image Process. 27(3): 1152-1163 (2018) - [j74]Xiang Zhang, Jiarui Sun, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao:
Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding. IEEE Trans. Image Process. 27(8): 3753-3765 (2018) - [j73]Xiaojie Guo, Zhouchen Lin:
Low-Rank Matrix Recovery Via Robust Outlier Estimation. IEEE Trans. Image Process. 27(11): 5316-5327 (2018) - [c78]Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis. AAAI 2018: 3714-3721 - [c77]Huan Li, Zhouchen Lin:
Construction of Incoherent Dictionaries via Direct Babel Function Minimization. ACML 2018: 598-613 - [c76]Huan Li, Yibo Yang, Dongmin Chen, Zhouchen Lin:
Optimization Algorithm Inspired Deep Neural Network Structure Design. ACML 2018: 614-629 - [c75]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Joint Dictionary Learning and Semantic Constrained Latent Subspace Projection for Cross-Modal Retrieval. CIKM 2018: 1663-1666 - [c74]Yibo Yang, Zhisheng Zhong, Tiancheng Shen, Zhouchen Lin:
Convolutional Neural Networks With Alternately Updated Clique. CVPR 2018: 2413-2422 - [c73]Xia Li, Jianlong Wu, Zhouchen Lin, Hong Liu, Hongbin Zha:
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining. ECCV (7) 2018: 262-277 - [c72]Chen Xu, Jianqiang Yao, Zhouchen Lin, Wenwu Ou, Yuanbin Cao, Zhirong Wang, Hongbin Zha:
Alternating Multi-bit Quantization for Recurrent Neural Networks. ICLR (Poster) 2018 - [c71]Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements. IJCAI 2018: 2504-2510 - [c70]Zhisheng Zhong, Tiancheng Shen, Yibo Yang, Zhouchen Lin, Chao Zhang:
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution. NeurIPS 2018: 165-175 - [c69]Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang:
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator. NeurIPS 2018: 687-697 - [i45]Chen Xu, Jianqiang Yao, Zhouchen Lin, Wenwu Ou, Yuanbin Cao, Zhirong Wang, Hongbin Zha:
Alternating Multi-bit Quantization for Recurrent Neural Networks. CoRR abs/1802.00150 (2018) - [i44]Cong Fang, Yameng Huang, Zhouchen Lin:
Accelerating Asynchronous Algorithms for Convex Optimization by Momentum Compensation. CoRR abs/1802.09747 (2018) - [i43]Yibo Yang, Zhisheng Zhong, Tiancheng Shen, Zhouchen Lin:
Convolutional Neural Networks with Alternately Updated Clique. CoRR abs/1802.10419 (2018) - [i42]Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan:
Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm. CoRR abs/1804.03728 (2018) - [i41]Canyi Lu, Jiashi Feng, Zhouchen Lin, Tao Mei, Shuicheng Yan:
Subspace Clustering by Block Diagonal Representation. CoRR abs/1805.09243 (2018) - [i40]Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements. CoRR abs/1806.02511 (2018) - [i39]Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang:
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator. CoRR abs/1807.01695 (2018) - [i38]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Essential Tensor Learning for Multi-view Spectral Clustering. CoRR abs/1807.03602 (2018) - [i37]Xia Li, Jianlong Wu, Zhouchen Lin, Hong Liu, Hongbin Zha:
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining. CoRR abs/1807.05698 (2018) - [i36]Risheng Liu, Shichao Cheng, Yi He, Xin Fan, Zhouchen Lin, Zhongxuan Luo:
On the Convergence of Learning-based Iterative Methods for Nonconvex Inverse Problems. CoRR abs/1808.05331 (2018) - [i35]Zhisheng Zhong, Tiancheng Shen, Yibo Yang, Zhouchen Lin, Chao Zhang:
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution. CoRR abs/1809.04508 (2018) - [i34]Huan Li, Yibo Yang, Dongmin Chen, Zhouchen Lin:
Optimization Algorithm Inspired Deep Neural Network Structure Design. CoRR abs/1810.01638 (2018) - [i33]Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin:
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. CoRR abs/1810.05186 (2018) - [i32]Jia Li, Cong Fang, Zhouchen Lin:
Lifted Proximal Operator Machines. CoRR abs/1811.01501 (2018) - 2017
- [j72]Yisong Chen, Antoni B. Chan, Zhouchen Lin, Kenji Suzuki, Guoping Wang:
Efficient tree-structured SfM by RANSAC generalized Procrustes analysis. Comput. Vis. Image Underst. 157: 179-189 (2017) - [j71]Jianlong Wu, Zhouchen Lin, Wenming Zheng, Hongbin Zha:
Locality-constrained linear coding based bi-layer model for multi-view facial expression recognition. Neurocomputing 239: 143-152 (2017) - [j70]Cong Fang, Zhenyu Zhao, Pan Zhou, Zhouchen Lin:
Feature learning via partial differential equation with applications to face recognition. Pattern Recognit. 69: 14-25 (2017) - [j69]Yang Lin, Zhouchen Lin, Hongbin Zha:
The Shape Interaction Matrix-Based Affine Invariant Mismatch Removal for Partial-Duplicate Image Search. IEEE Trans. Image Process. 26(2): 561-573 (2017) - [j68]Jia Li, Chen-Yan Bai, Zhouchen Lin, Jian Yu:
Automatic Design of High-Sensitivity Color Filter Arrays With Panchromatic Pixels. IEEE Trans. Image Process. 26(2): 870-883 (2017) - [j67]Pan Zhou, Chao Zhang, Zhouchen Lin:
Bilevel Model-Based Discriminative Dictionary Learning for Recognition. IEEE Trans. Image Process. 26(3): 1173-1187 (2017) - [j66]Jia Li, Chen-Yan Bai, Zhouchen Lin, Jian Yu:
Optimized Color Filter Arrays for Sparse Representation-Based Demosaicking. IEEE Trans. Image Process. 26(5): 2381-2393 (2017) - [j65]Liansheng Zhuang, Zihan Zhou, Shenghua Gao, Jingwen Yin, Zhouchen Lin, Yi Ma:
Label Information Guided Graph Construction for Semi-Supervised Learning. IEEE Trans. Image Process. 26(9): 4182-4192 (2017) - [c68]Cong Fang, Zhouchen Lin:
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization. AAAI 2017: 794-800 - [c67]Chen Xu, Zhouchen Lin, Hongbin Zha:
A Unified Convex Surrogate for the Schatten-p Norm. AAAI 2017: 926-932 - [c66]Hongyang Zhang, Shan You, Zhouchen Lin, Chao Xu:
Fast Compressive Phase Retrieval under Bounded Noise. AAAI 2017: 2884-2890 - [c65]Xiang Zhang, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao:
Globally Variance-Constrained Sparse Representation for Rate-Distortion Optimized Image Representation. DCC 2017: 380-389 - [c64]Xiaojie Guo, Zhouchen Lin:
ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery. IJCAI 2017: 1746-1752 - [c63]Yang Lin, Li Yang, Zhouchen Lin, Tong Lin, Hongbin Zha:
Factorization for projective and metric reconstruction via truncated nuclear norm. IJCNN 2017: 470-477 - [c62]Cong Fang, Feng Cheng, Zhouchen Lin:
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers. NIPS 2017: 4476-4485 - [c61]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Joint Latent Subspace Learning and Regression for Cross-Modal Retrieval. SIGIR 2017: 917-920 - [i31]Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan:
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization. CoRR abs/1708.04181 (2017) - [i30]Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis. CoRR abs/1712.02979 (2017) - 2016
- [j64]Liansheng Zhuang, Jingjing Wang, Zhouchen Lin, Allen Y. Yang, Yi Ma, Nenghai Yu:
Locality-preserving low-rank representation for graph construction from nonlinear manifolds. Neurocomputing 175: 715-722 (2016) - [j63]Zhenyu Zhao, Zhouchen Lin, Yi Wu:
A fast alternating time-splitting approach for learning partial differential equations. Neurocomputing 185: 171-182 (2016) - [j62]Jia Li, Chen-Yan Bai, Zhouchen Lin, Jian Yu:
Penrose high-dynamic-range imaging. J. Electronic Imaging 25(3): 033024 (2016) - [j61]Ming Yin, Junbin Gao, Zhouchen Lin:
Laplacian Regularized Low-Rank Representation and Its Applications. IEEE Trans. Pattern Anal. Mach. Intell. 38(3): 504-517 (2016) - [j60]Zhouchen Lin, Yameng Huang:
Fast Multidimensional Ellipsoid-Specific Fitting by Alternating Direction Method of Multipliers. IEEE Trans. Pattern Anal. Mach. Intell. 38(5): 1021-1026 (2016) - [j59]Risheng Liu, Guangyu Zhong, Junjie Cao, Zhouchen Lin, Shiguang Shan, Zhongxuan Luo:
Learning to Diffuse: A New Perspective to Design PDEs for Visual Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 38(12): 2457-2471 (2016) - [j58]Qi Li, Zhenan Sun, Zhouchen Lin, Ran He, Tieniu Tan:
Transformation invariant subspace clustering. Pattern Recognit. 59: 142-155 (2016) - [j57]Canyi Lu, Jinhui Tang, Shuicheng Yan, Zhouchen Lin:
Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm. IEEE Trans. Image Process. 25(2): 829-839 (2016) - [j56]Chen-Yan Bai, Jia Li, Zhouchen Lin, Jian Yu:
Automatic Design of Color Filter Arrays in the Frequency Domain. IEEE Trans. Image Process. 25(4): 1793-1807 (2016) - [j55]Canyi Lu, Shuicheng Yan, Zhouchen Lin:
Convex Sparse Spectral Clustering: Single-View to Multi-View. IEEE Trans. Image Process. 25(6): 2833-2843 (2016) - [j54]Hongyang Zhang, Zhouchen Lin, Chao Zhang:
Completing Low-Rank Matrices With Corrupted Samples From Few Coefficients in General Basis. IEEE Trans. Inf. Theory 62(8): 4748-4768 (2016) - [j53]Pan Zhou, Zhouchen Lin, Chao Zhang:
Integrated Low-Rank-Based Discriminative Feature Learning for Recognition. IEEE Trans. Neural Networks Learn. Syst. 27(5): 1080-1093 (2016) - [j52]Yifan Fu, Junbin Gao, David Tien, Zhouchen Lin, Xia Hong:
Tensor LRR and Sparse Coding-Based Subspace Clustering. IEEE Trans. Neural Networks Learn. Syst. 27(10): 2120-2133 (2016) - [c60]Canyi Lu, Huan Li, Zhouchen Lin, Shuicheng Yan:
Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting. AAAI 2016: 739-745 - [c59]Chen Xu, Zhouchen Lin, Zhenyu Zhao, Hongbin Zha:
Relaxed Majorization-Minimization for Non-Smooth and Non-Convex Optimization. AAAI 2016: 812-818 - [c58]Jin-shan Pan, Zhouchen Lin, Zhixun Su, Ming-Hsuan Yang:
Robust Kernel Estimation with Outliers Handling for Image Deblurring. CVPR 2016: 2800-2808 - [c57]Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan:
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization. CVPR 2016: 5249-5257 - [c56]Li Shen, Zhouchen Lin, Qingming Huang:
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks. ECCV (7) 2016: 467-482 - [c55]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Multi-view common space learning for emotion recognition in the wild. ICMI 2016: 464-471 - [c54]Yuqing Hou, Zhouchen Lin, Jin-ge Yao:
Subspace Clustering Based Tag Sharing for Inductive Tag Matrix Refinement with Complex Errors. SIGIR 2016: 1013-1016 - [i29]Canyi Lu, Jiashi Feng, Shuicheng Yan, Zhouchen Lin:
A Unified Alternating Direction Method of Multipliers by Majorization Minimization. CoRR abs/1607.02584 (2016) - [i28]Xiang Zhang, Jiarui Sun, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao:
Globally Variance-Constrained Sparse Representation for Image Set Compression. CoRR abs/1608.04902 (2016) - [i27]Chen Xu, Zhouchen Lin, Hongbin Zha:
A Unified Convex Surrogate for the Schatten-$p$ Norm. CoRR abs/1611.08372 (2016) - 2015
- [j51]Zhenyu Zhao, Cong Fang, Zhouchen Lin, Yi Wu:
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations. Neurocomputing 168: 23-34 (2015) - [j50]Zhouchen Lin, Risheng Liu, Huan Li:
Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning. Mach. Learn. 99(2): 287-325 (2015) - [j49]Hongyang Zhang, Zhouchen Lin, Chao Zhang, Junbin Gao:
Relations Among Some Low-Rank Subspace Recovery Models. Neural Comput. 27(9): 1915-1950 (2015) - [j48]Jianjun Qian, Lei Luo, Jian Yang, Fanlong Zhang, Zhouchen Lin:
Robust nuclear norm regularized regression for face recognition with occlusion. Pattern Recognit. 48(10): 3145-3159 (2015) - [j47]Canyi Lu, Zhouchen Lin, Shuicheng Yan:
Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization. IEEE Trans. Image Process. 24(2): 646-654 (2015) - [j46]Chen-Yan Bai, Jia Li, Zhouchen Lin, Jian Yu, Yen-Wei Chen:
Penrose Demosaicking. IEEE Trans. Image Process. 24(5): 1672-1684 (2015) - [j45]Li Shen, Gang Sun, Qingming Huang, Shuhui Wang, Zhouchen Lin, Enhua Wu:
Multi-Level Discriminative Dictionary Learning With Application to Large Scale Image Classification. IEEE Trans. Image Process. 24(10): 3109-3123 (2015) - [j44]Liansheng Zhuang, Shenghua Gao, Jinhui Tang, Jingjing Wang, Zhouchen Lin, Yi Ma, Nenghai Yu:
Constructing a Nonnegative Low-Rank and Sparse Graph With Data-Adaptive Features. IEEE Trans. Image Process. 24(11): 3717-3728 (2015) - [j43]Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi, Yi Guo:
Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering. IEEE Trans. Image Process. 24(12): 4918-4933 (2015) - [c53]Canyi Lu, Changbo Zhu, Chunyan Xu, Shuicheng Yan, Zhouchen Lin:
Generalized Singular Value Thresholding. AAAI 2015: 1805-1811 - [c52]Hongyang Zhang, Zhouchen Lin, Chao Zhang, Edward Y. Chang:
Exact Recoverability of Robust PCA via Outlier Pursuit with Tight Recovery Bounds. AAAI 2015: 3143-3149 - [c51]Baohua Li, Ying Zhang, Zhouchen Lin, Huchuan Lu:
Subspace clustering by Mixture of Gaussian Regression. CVPR 2015: 2094-2102 - [c50]Zhizhong Li, Deli Zhao, Zhouchen Lin, Edward Y. Chang:
A new retraction for accelerating the Riemannian three-factor low-rank matrix completion algorithm. CVPR 2015: 4530-4538 - [c49]Chun-Guang Li, Zhouchen Lin, Honggang Zhang, Jun Guo:
Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning. ICCV 2015: 2767-2775 - [c48]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Multiple Models Fusion for Emotion Recognition in the Wild. ICMI 2015: 475-481 - [c47]