Geometric Conditions for Subspace-Sparse Recovery. - Chong You; René Vidal (ICML, 2015)

Sparse Subspace Clustering by Orthogonal Matching Pursuit. - Chong You; René Vidal (CoRR, 2015)

Subspace-Sparse Representation. - Chong You; René Vidal (CoRR, 2015)

A divide-and-conquer framework for large-scale subspace clustering. - Chong You; Claire Donnat; Daniel P. Robinson; René Vidal (ACSSC, 2016)

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. - Chong You; Chun-Guang Li; Daniel P. Robinson; René Vidal (CVPR, 2016)

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. - Chong You; Daniel P. Robinson; René Vidal (CVPR, 2016)

On generalized degrees of freedom with application in linear mixed models selection. - Chong You; Samuel Müller 001; John T. Ormerod (Stat. Comput., 2016)

Provable Self-Representation Based Outlier Detection in a Union of Subspaces. - Chong You; Daniel P. Robinson; René Vidal (CVPR, 2017)

Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework. - Chun-Guang Li; Chong You; René Vidal (IEEE Trans. Image Process., 2017)

A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. - Chong You; Chi Li; Daniel P. Robinson; René Vidal (ECCV (9), 2018)

A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis. - Hao Jiang; Daniel P. Robinson; René Vidal; Chong You (Comput. Optim. Appl., 2018)

On Geometric Analysis of Affine Sparse Subspace Clustering. - Chun-Guang Li; Chong You; René Vidal (IEEE J. Sel. Top. Signal Process., 2018)

Self-Supervised Convolutional Subspace Clustering Network. - Junjian Zhang; Chun-Guang Li; Chong You; Xianbiao Qi; Honggang Zhang 002; Jun Guo 002; Zhouchen Lin (CVPR, 2019)

Is an Affine Constraint Needed for Affine Subspace Clustering? - Chong You; Chun-Guang Li; Daniel P. Robinson; René Vidal (ICCV, 2019)

Classifying and Comparing Approaches to Subspace Clustering with Missing Data. - Connor Lane; Ron Boger; Chong You; Manolis C. Tsakiris; Benjamin D. Haeffele; René Vidal (ICCV Workshops, 2019)

Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. - Daniel P. Robinson; René Vidal; Chong You (CoRR, 2019)

Stochastic Sparse Subspace Clustering. - Ying Chen; Chun-Guang Li; Chong You (CVPR, 2020)

Spatial Analysis of the Correlation between Scintillation Parameters and MP&ROTI. - Chendong Li; Craig Matthew Hancock; Sreeja Vadakke Veettil; Chong You (ENC, 2020)

Deep Isometric Learning for Visual Recognition. - Haozhi Qi; Chong You; Xiaolong Wang 004; Yi Ma 001; Jitendra Malik (ICML, 2020)

Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. - Zitong Yang; Yaodong Yu; Chong You; Jacob Steinhardt; Yi Ma 001 (ICML, 2020)

Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. - Chong You; Zhihui Zhu; Qing Qu 001; Yi Ma 001 (NeurIPS, 2020)

Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. - Yaodong Yu; Kwan Ho Ryan Chan; Chong You; Chaobing Song; Yi Ma 001 (NeurIPS, 2020)

Deep Networks from the Principle of Rate Reduction. - Kwan Ho Ryan Chan; Yaodong Yu; Chong You; Haozhi Qi; John Wright 001; Yi Ma 001 (CoRR, 2020)

Analysis of the Relationship between Scintillation Parameters, Multipath and ROTI. - Chendong Li; Craig M. Hancock; Nicholas A. S. Hamm; Sreeja Vadakke Veettil; Chong You (Sensors, 2020)

Incremental Learning via Rate Reduction. - Ziyang Wu; Christina Baek; Chong You; Yi Ma 001 (CVPR, 2021)

Learning a Self-Expressive Network for Subspace Clustering. - Shangzhi Zhang; Chong You; René Vidal; Chun-Guang Li (CVPR, 2021)

A Critique of Self-Expressive Deep Subspace Clustering. - Benjamin David Haeffele; Chong You; René Vidal (ICLR, 2021)

A Nullspace Property for Subspace-Preserving Recovery. - Mustafa Devrim Kaba; Chong You; Daniel P. Robinson; Enrique Mallada; René Vidal (ICML, 2021)

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. - Sheng Liu; Xiao Li 026; Yuexiang Zhai; Chong You; Zhihui Zhu; Carlos Fernandez-Granda; Qing Qu 001 (NeurIPS, 2021)

A Geometric Analysis of Neural Collapse with Unconstrained Features. - Zhihui Zhu; Tianyu Ding; Jinxin Zhou; Xiao Li 026; Chong You; Jeremias Sulam; Qing Qu 001 (NeurIPS, 2021)

A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening. - Lei Cao; Jinying Yang; Zhiwei Rong; Lulu Li; Bairong Xia; Chong You; Ge Lou; Lei Jiang; Chun Du; Hongxue Meng; Wenjie Wang; Meng Wang; et al. (Medical Image Anal., 2021)

Robust Training under Label Noise by Over-parameterization. - Sheng Liu; Zhihui Zhu; Qing Qu 001; Chong You (ICML, 2022)

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. - Jinxin Zhou; Xiao Li 026; Tianyu Ding; Chong You; Qing Qu 001; Zhihui Zhu (ICML, 2022)

Revisiting Sparse Convolutional Model for Visual Recognition. - Xili Dai; Mingyang Li; Pengyuan Zhai; Shengbang Tong; Xingjian Gao; Shao-Lun Huang; Zhihui Zhu; Chong You; Yi Ma 001 (NeurIPS, 2022)

Are All Losses Created Equal: A Neural Collapse Perspective. - Jinxin Zhou; Chong You; Xiao Li 026; Kangning Liu; Sheng Liu; Qing Qu 001; Zhihui Zhu (NeurIPS, 2022)

Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. - 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 (CoRR, 2022)

ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. - Kwan Ho Ryan Chan; Yaodong Yu; Chong You; Haozhi Qi; John Wright 001; Yi Ma 001 (J. Mach. Learn. Res., 2022)

Recovery and Generalization in Over-Realized Dictionary Learning. - Jeremias Sulam; Chong You; Zhihui Zhu (J. Mach. Learn. Res., 2022)

Integration of Computer Virtual Reality Technology to College Physical Education. - Yuhuan Feng; Chong You; Yanbing Li; Ya Zhang; Qingxia Wang (J. Web Eng., 2022)

Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. - Chong You; Chi Li; Daniel P. Robinson; René Vidal (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. - 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 (ICLR, 2023)

Teacher Guided Training: An Efficient Framework for Knowledge Transfer. - Manzil Zaheer; Ankit Singh Rawat; Seungyeon Kim 001; Chong You; Himanshu Jain; Andreas Veit; Rob Fergus; Sanjiv Kumar (ICLR, 2023)

It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models. - Lin Chen; Michal Lukasik; Wittawat Jitkrittum; Chong You; Sanjiv Kumar (CoRR, 2023)

An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression. - Chong You; John T. Ormerod; Xiangyang Li; Cheng Heng Pang; Xiao-Hua Zhou (J. Comput. Graph. Stat., 2023)

Deep Self-expressive Learning. - Chen Zhao; Chun-Guang Li; Wei He; Chong You (CPAL, 2024)

On Bias-Variance Alignment in Deep Models. - Lin Chen; Michal Lukasik; Wittawat Jitkrittum; Chong You; Sanjiv Kumar (ICLR, 2024)

Functional Interpolation for Relative Positions improves Long Context Transformers. - Shanda Li; Chong You; Guru Guruganesh; Joshua Ainslie; Santiago Ontañón; Manzil Zaheer; Sumit Sanghai; Yiming Yang; Sanjiv Kumar; Srinadh Bhojanapalli (ICLR, 2024)

Generalized Neural Collapse for a Large Number of Classes. - Jiachen Jiang; Jinxin Zhou; Peng Wang 098; Qing Qu 001; Dustin G. Mixon; Chong You; Zhihui Zhu (ICML, 2024)

HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference. - Yashas Samaga; Varun Yerram; Chong You; Srinadh Bhojanapalli; Sanjiv Kumar; Prateek Jain 002; Praneeth Netrapalli (CoRR, 2024)

Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models. - Haotian Ye; Himanshu Jain; Chong You; Ananda Theertha Suresh; Haowei Lin; James Zou 001; Felix X. Yu (AISTATS, 2025)

Spark Transformer: Reactivating Sparsity in FFN and Attention. - Chong You; Kan Wu; Zhipeng Jia; Lin Chen; Srinadh Bhojanapalli; Jiaxian Guo; Utku Evci; Jan Wassenberg; Praneeth Netrapalli; Jeremiah J. Willcock; Suvinay Subramanian; Felix Chern; et al. (CoRR, 2025)