You, Chong

32 publications

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

NeurIPS 2025 Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix X. Yu, Sanjiv Kumar

NeurIPS 2025 Scalable In-Context Ranking with Generative Models Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit S Dhillon, Felix X. Yu

NeurIPS 2025 Spark Transformer: Reactivating Sparsity in Transformer 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, Alek Andreev, Shreya Pathak, Felix X. Yu, Prateek Jain, David E Culler, Henry Levy, Sanjiv Kumar

CPAL 2024 Deep Self-Expressive Learning Chen Zhao, Chun-Guang Li, Wei He, Chong You

ICLR 2024 Functional Interpolation for Relative Positions Improves Long Context Transformers Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontanon, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli

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

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

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

ICLR 2023 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 Yu, Ruiqi Guo, Sanjiv Kumar

NeurIPS 2022 Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu

ICML 2022 On the Optimization Landscape of Neural Collapse Under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu

JMLR 2022 Recovery and Generalization in Over-Realized Dictionary Learning Jeremias Sulam, Chong You, Zhihui Zhu

JMLR 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, Yi Ma

NeurIPS 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

ICML 2022 Robust Training Under Label Noise by Over-Parameterization Sheng Liu, Zhihui Zhu, Qing Qu, Chong You

ICLR 2021 A Critique of Self-Expressive Deep Subspace Clustering Benjamin David Haeffele, Chong You, Rene Vidal

NeurIPS 2021 A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu

ICML 2021 A Nullspace Property for Subspace-Preserving Recovery Mustafa D Kaba, Chong You, Daniel P Robinson, Enrique Mallada, Rene Vidal

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

CVPR 2021 Incremental Learning via Rate Reduction Ziyang Wu, Christina Baek, Chong You, Yi Ma

CVPR 2021 Learning a Self-Expressive Network for Subspace Clustering Shangzhi Zhang, Chong You, Rene Vidal, Chun-Guang Li

ICML 2020 Deep Isometric Learning for Visual Recognition Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik

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

ICML 2020 Rethinking Bias-Variance Trade-Off for Generalization of Neural Networks Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma

NeurIPS 2020 Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-Parameterization Chong You, Zhihui Zhu, Qing Qu, Yi Ma

ICCVW 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

ECCV 2018 Scalable Exemplar-Based Subspace Clustering on Class-Imbalanced Data Chong You, Chi Li, Daniel P. Robinson, Rene Vidal

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

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

CVPR 2016 Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit Chong You, Daniel Robinson, Rene Vidal

ICML 2015 Geometric Conditions for Subspace-Sparse Recovery Chong You, Rene Vidal