Chong You

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 73

Top Topics

Convolutional Network

Subspace Clustering

Orthogonal Matching Pursuit

Top Venues

Publications

Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
On Bias-Variance Alignment in Deep Models. ICLR (2024)
Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
Functional Interpolation for Relative Positions improves Long Context Transformers. ICLR (2024)
Yashas Samaga, Varun Yerram, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference. CoRR (2024)
Chong You, John T. Ormerod, Xiangyang Li, Cheng Heng Pang, Xiao-Hua Zhou
An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression. J. Comput. Graph. Stat. 32 (3) (2023)
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. ICLR (2023)
Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
Functional Interpolation for Relative Positions Improves Long Context Transformers. CoRR (2023)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. ICLR (2023)
Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models. CoRR (2023)
Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin Mixon, Chong You, Zhihui Zhu
Generalized Neural Collapse for a Large Number of Classes. CoRR (2023)
Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. J. Mach. Learn. Res. 23 (2022)
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar
Teacher Guided Training: An Efficient Framework for Knowledge Transfer. CoRR (2022)
Sheng Liu, Zhihui Zhu, Qing Qu, Chong You
Robust Training under Label Noise by Over-parameterization. CoRR (2022)
Jeremias Sulam, Chong You, Zhihui Zhu
Recovery and Generalization in Over-Realized Dictionary Learning. J. Mach. Learn. Res. 23 (2022)
Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. CoRR (2022)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 44 (5) (2022)
Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. ICML (2022)
Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
Are All Losses Created Equal: A Neural Collapse Perspective. CoRR (2022)
Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
Are All Losses Created Equal: A Neural Collapse Perspective. NeurIPS (2022)
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix X. Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. CoRR (2022)
Xili Dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao, Shao-Lun Huang, Zhihui Zhu, Chong You, Yi Ma
Revisiting Sparse Convolutional Model for Visual Recognition. NeurIPS (2022)
Yuhuan Feng, Chong You, Yanbing Li, Ya Zhang, Qingxia Wang
Integration of Computer Virtual Reality Technology to College Physical Education. J. Web Eng. 21 (7) (2022)
Xili Dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao, Shao-Lun Huang, Zhihui Zhu, Chong You, Yi Ma
Revisiting Sparse Convolutional Model for Visual Recognition. CoRR (2022)
Sheng Liu, Zhihui Zhu, Qing Qu, Chong You
Robust Training under Label Noise by Over-parameterization. ICML (2022)
Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. NeurIPS (2021)
Lei Cao, Jinying Yang, Zhiwei Rong, Lulu Li, Bairong Xia, Chong You, Ge Lou, Lei Jiang, Chun Du, Hongxue Meng, Wenjie Wang, Meng Wang, Kang Li, Yan Hou
A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening. Medical Image Anal. 73 (2021)
Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. CoRR (2021)
Ziyang Wu, Christina Baek, Chong You, Yi Ma
Incremental Learning via Rate Reduction. CVPR (2021)
Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
A Geometric Analysis of Neural Collapse with Unconstrained Features. CoRR (2021)
Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal
A Nullspace Property for Subspace-Preserving Recovery. ICML (2021)
Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
A Geometric Analysis of Neural Collapse with Unconstrained Features. NeurIPS (2021)
Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li
Learning a Self-Expressive Network for Subspace Clustering. CVPR (2021)
Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li
Learning a Self-Expressive Network for Subspace Clustering. CoRR (2021)
Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. CoRR (2021)
Benjamin David Haeffele, Chong You, René Vidal
A Critique of Self-Expressive Deep Subspace Clustering. ICLR (2021)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. CoRR (2020)
Chong You, Zhihui Zhu, Qing Qu, Yi Ma
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. CoRR (2020)
Chong You, Zhihui Zhu, Qing Qu, Yi Ma
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. NeurIPS (2020)
Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. ICML (2020)
Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. NeurIPS (2020)
Jeremias Sulam, Chong You, Zhihui Zhu
Recovery and Generalization in Over-Realized Dictionary Learning. CoRR (2020)
Ying Chen, Chun-Guang Li, Chong You
Stochastic Sparse Subspace Clustering. CoRR (2020)
Chendong Li, Craig Matthew Hancock, Sreeja Vadakke Veettil, Chong You
Spatial Analysis of the Correlation between Scintillation Parameters and MP&ROTI. ENC (2020)
Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. CoRR (2020)
Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik
Deep Isometric Learning for Visual Recognition. CoRR (2020)
Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. CoRR (2020)
Benjamin D. Haeffele, Chong You, René Vidal
A Critique of Self-Expressive Deep Subspace Clustering. CoRR (2020)
Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik
Deep Isometric Learning for Visual Recognition. ICML (2020)
Ziyang Wu, Christina Baek, Chong You, Yi Ma
Incremental Learning via Rate Reduction. CoRR (2020)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Is an Affine Constraint Needed for Affine Subspace Clustering? CoRR (2020)
Chendong Li, Craig M. Hancock, Nicholas A. S. Hamm, Sreeja Vadakke Veettil, Chong You
Analysis of the Relationship between Scintillation Parameters, Multipath and ROTI. Sensors 20 (10) (2020)
Ying Chen, Chun-Guang Li, Chong You
Stochastic Sparse Subspace Clustering. CVPR (2020)
Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma
Deep Networks from the Principle of Rate Reduction. CoRR (2020)
Connor Lane, Ron Boger, Chong You, Manolis C. Tsakiris, Benjamin D. Haeffele, René Vidal
Classifying and Comparing Approaches to Subspace Clustering with Missing Data. ICCV Workshops (2019)
Daniel P. Robinson, René Vidal, Chong You
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. CoRR (2019)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV (2019)
Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin
Self-Supervised Convolutional Subspace Clustering Network. CVPR (2019)
Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin
Self-Supervised Convolutional Subspace Clustering Network. CoRR (2019)
Hao Jiang, Daniel P. Robinson, René Vidal, Chong You
A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis. Comput. Optim. Appl. 70 (2) (2018)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. ECCV (9) (2018)
Chun-Guang Li, Chong You, René Vidal
On Geometric Analysis of Affine Sparse Subspace Clustering. CoRR (2018)
Chun-Guang Li, Chong You, René Vidal
On Geometric Analysis of Affine Sparse Subspace Clustering. IEEE J. Sel. Top. Signal Process. 12 (6) (2018)
Chong You, Daniel P. Robinson, René Vidal
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CoRR (2017)
Chun-Guang Li, Chong You, René Vidal
Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework. IEEE Trans. Image Process. 26 (6) (2017)
Chong You, Daniel P. Robinson, René Vidal
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CVPR (2017)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CVPR (2016)
Chong You, Samuel Müller, John T. Ormerod
On generalized degrees of freedom with application in linear mixed models selection. Stat. Comput. 26 (1-2) (2016)
Chong You, Daniel P. Robinson, René Vidal
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. CVPR (2016)
Chong You, Claire Donnat, Daniel P. Robinson, René Vidal
A divide-and-conquer framework for large-scale subspace clustering. ACSSC (2016)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CoRR (2016)
Chun-Guang Li, Chong You, René Vidal
Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework. CoRR (2016)
Chong You, René Vidal
Sparse Subspace Clustering by Orthogonal Matching Pursuit. CoRR (2015)
Chong You, René Vidal
Subspace-Sparse Representation. CoRR (2015)
Chong You, René Vidal
Geometric Conditions for Subspace-Sparse Recovery. ICML (2015)