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2020 – today
- 2024
[c30]Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar:
On Bias-Variance Alignment in Deep Models. ICLR 2024- [c29]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 - [c28]Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu
, Dustin G. Mixon, Chong You, Zhihui Zhu:
Generalized Neural Collapse for a Large Number of Classes. ICML 2024 - [i33]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 abs/2402.09360 (2024) - 2023
- [j11]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): 782-792 (2023) - [c27]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 - [c26]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 - [i32]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 abs/2310.04418 (2023) - [i31]Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin G. Mixon, Chong You, Zhihui Zhu:
Generalized Neural Collapse for a Large Number of Classes. CoRR abs/2310.05351 (2023) - [i30]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 abs/2310.09250 (2023) - 2022
- [j10]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: 114:1-114:103 (2022) - [j9]Jeremias Sulam, Chong You, Zhihui Zhu:
Recovery and Generalization in Over-Realized Dictionary Learning. J. Mach. Learn. Res. 23: 135:1-135:23 (2022) - [j8]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): 2049-2072 (2022) - [j7]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): 2698-2711 (2022) - [c25]Sheng Liu, Zhihui Zhu, Qing Qu, Chong You:
Robust Training under Label Noise by Over-parameterization. ICML 2022: 14153-14172 - [c24]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: 27179-27202 - [c23]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 - [c22]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 - [i29]Sheng Liu, Zhihui Zhu, Qing Qu, Chong You:
Robust Training under Label Noise by Over-parameterization. CoRR abs/2202.14026 (2022) - [i28]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 abs/2203.01238 (2022) - [i27]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 abs/2208.06825 (2022) - [i26]Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu:
Are All Losses Created Equal: A Neural Collapse Perspective. CoRR abs/2210.02192 (2022) - [i25]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:
Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. CoRR abs/2210.06313 (2022) - [i24]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 abs/2210.12945 (2022) - 2021
- [j6]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: 102197 (2021) - [c21]Ziyang Wu, Christina Baek, Chong You, Yi Ma:
Incremental Learning via Rate Reduction. CVPR 2021: 1125-1133 - [c20]Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li:
Learning a Self-Expressive Network for Subspace Clustering. CVPR 2021: 12393-12403 - [c19]Benjamin David Haeffele, Chong You, René Vidal:
A Critique of Self-Expressive Deep Subspace Clustering. ICLR 2021 - [c18]Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal:
A Nullspace Property for Subspace-Preserving Recovery. ICML 2021: 5180-5188 - [c17]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: 28919-28928 - [c16]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: 29820-29834 - [i23]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 abs/2103.00673 (2021) - [i22]Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu:
A Geometric Analysis of Neural Collapse with Unconstrained Features. CoRR abs/2105.02375 (2021) - [i21]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 abs/2105.10446 (2021) - [i20]Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li:
Learning a Self-Expressive Network for Subspace Clustering. CoRR abs/2110.04318 (2021) - 2020
- [j5]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): 2877 (2020) - [c15]Ying Chen, Chun-Guang Li, Chong You:
Stochastic Sparse Subspace Clustering. CVPR 2020: 4154-4163 - [c14]Chendong Li, Craig Matthew Hancock, Sreeja Vadakke Veettil, Chong You:
Spatial Analysis of the Correlation between Scintillation Parameters and MP&ROTI. ENC 2020: 1-9 - [c13]Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik:
Deep Isometric Learning for Visual Recognition. ICML 2020: 7824-7835 - [c12]Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma:
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. ICML 2020: 10767-10777 - [c11]Chong You, Zhihui Zhu, Qing Qu, Yi Ma:
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. NeurIPS 2020 - [c10]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 - [i19]Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma:
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks. CoRR abs/2002.11328 (2020) - [i18]Ying Chen, Chun-Guang Li, Chong You:
Stochastic Sparse Subspace Clustering. CoRR abs/2005.01449 (2020) - [i17]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Is an Affine Constraint Needed for Affine Subspace Clustering? CoRR abs/2005.03888 (2020) - [i16]Chong You, Chi Li, Daniel P. Robinson, René Vidal:
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. CoRR abs/2006.04246 (2020) - [i15]Jeremias Sulam, Chong You, Zhihui Zhu:
Recovery and Generalization in Over-Realized Dictionary Learning. CoRR abs/2006.06179 (2020) - [i14]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 abs/2006.08558 (2020) - [i13]Chong You, Zhihui Zhu, Qing Qu, Yi Ma:
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. CoRR abs/2006.08857 (2020) - [i12]Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik:
Deep Isometric Learning for Visual Recognition. CoRR abs/2006.16992 (2020) - [i11]Benjamin D. Haeffele, Chong You, René Vidal:
A Critique of Self-Expressive Deep Subspace Clustering. CoRR abs/2010.03697 (2020) - [i10]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
Deep Networks from the Principle of Rate Reduction. CoRR abs/2010.14765 (2020) - [i9]Ziyang Wu, Christina Baek, Chong You, Yi Ma:
Incremental Learning via Rate Reduction. CoRR abs/2011.14593 (2020)
2010 – 2019
- 2019
- [c9]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 - [c8]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV 2019: 9914-9923 - [c7]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: 669-677 - [i8]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) - [i7]Daniel P. Robinson, René Vidal, Chong You:
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. CoRR abs/1912.13091 (2019) - 2018
- [j4]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): 395-418 (2018) - [j3]Chun-Guang Li, Chong You, René Vidal:
On Geometric Analysis of Affine Sparse Subspace Clustering. IEEE J. Sel. Top. Signal Process. 12(6): 1520-1533 (2018) - [c6]Chong You, Chi Li, Daniel P. Robinson, René Vidal:
A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. ECCV (9) 2018: 68-85 - [i6]Chun-Guang Li, Chong You, René Vidal:
On Geometric Analysis of Affine Sparse Subspace Clustering. CoRR abs/1808.05965 (2018) - 2017
- [j2]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): 2988-3001 (2017) - [c5]Chong You, Daniel P. Robinson, René Vidal:
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CVPR 2017: 4323-4332 - [i5]Chong You, Daniel P. Robinson, René Vidal:
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CoRR abs/1704.03925 (2017) - 2016
- [j1]Chong You, Samuel Müller, John T. Ormerod:
On generalized degrees of freedom with application in linear mixed models selection. Stat. Comput. 26(1-2): 199-210 (2016) - [c4]Chong You, Claire Donnat, Daniel P. Robinson, René Vidal:
A divide-and-conquer framework for large-scale subspace clustering. ACSSC 2016: 1014-1018 - [c3]Chong You, Daniel P. Robinson, René Vidal:
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. CVPR 2016: 3918-3927 - [c2]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CVPR 2016: 3928-3937 - [i4]Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal:
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CoRR abs/1605.02633 (2016) - [i3]Chun-Guang Li, Chong You, René Vidal:
Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework. CoRR abs/1610.05211 (2016) - 2015
- [c1]Chong You, René Vidal:
Geometric Conditions for Subspace-Sparse Recovery. ICML 2015: 1585-1593 - [i2]Chong You, René Vidal:
Sparse Subspace Clustering by Orthogonal Matching Pursuit. CoRR abs/1507.01238 (2015) - [i1]Chong You, René Vidal:
Subspace-Sparse Representation. CoRR abs/1507.01307 (2015)
Coauthor Index
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