Chong You

According to our database, Chong You authored at least 46 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference.

Yashas Samaga, Varun Yerram, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli

CoRR, 2024

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

Generalized Neural Collapse for a Large Number of Classes.

Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin Mixon, Chong You, Zhihui Zhu

CoRR, 2023

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

CoRR, 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

Proceedings of the Eleventh International Conference on Learning Representations, 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 X. Yu, Ruiqi Guo, Sanjiv Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

Integration of Computer Virtual Reality Technology to College Physical Education.

Yuhuan Feng, Chong You, Yanbing Li, Ya Zhang, Qingxia Wang

J. Web Eng., 2022

Recovery and Generalization in Over-Realized Dictionary Learning.

Jeremias Sulam, Chong You, Zhihui Zhu

J. Mach. Learn. Res., 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

J. Mach. Learn. Res., 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

Are All Losses Created Equal: A Neural Collapse Perspective.

Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Proceedings of the International Conference on Machine Learning, 2022

Robust Training under Label Noise by Over-parameterization.

Sheng Liu, Zhihui Zhu, Qing Qu, Chong You

Proceedings of the International Conference on Machine Learning, 2022

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, Kang Li, Yan Hou

Medical Image Anal., 2021

A Geometric Analysis of Neural Collapse with Unconstrained Features.

Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Nullspace Property for Subspace-Preserving Recovery.

Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal

Proceedings of the 38th International Conference on Machine Learning, 2021

A Critique of Self-Expressive Deep Subspace Clustering.

Benjamin David Haeffele, Chong You, René Vidal

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning a Self-Expressive Network for Subspace Clustering.

Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Incremental Learning via Rate Reduction.

Ziyang Wu, Christina Baek, Chong You, Yi Ma

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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

Deep Networks from the Principle of Rate Reduction.

Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization.

Chong You, Zhihui Zhu, Qing Qu, Yi Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rethinking Bias-Variance Trade-off for Generalization of Neural Networks.

Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma

Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Isometric Learning for Visual Recognition.

Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik

Proceedings of the 37th International Conference on Machine Learning, 2020

Spatial Analysis of the Correlation between Scintillation Parameters and MP&ROTI.

Chendong Li, Craig Matthew Hancock, Sreeja Vadakke Veettil, Chong You

Proceedings of the European Navigation Conference, 2020

Stochastic Sparse Subspace Clustering.

Ying Chen, Chun-Guang Li, Chong You

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis.

Daniel P. Robinson, René Vidal, Chong You

CoRR, 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

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Is an Affine Constraint Needed for Affine Subspace Clustering?

Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Self-Supervised Convolutional Subspace Clustering Network.

Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

On Geometric Analysis of Affine Sparse Subspace Clustering.

Chun-Guang Li, Chong You, René Vidal

IEEE J. Sel. Top. Signal Process., 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

A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data.

Chong You, Chi Li, Daniel P. Robinson, René Vidal

Proceedings of the Computer Vision - ECCV 2018, 2018

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

Provable Self-Representation Based Outlier Detection in a Union of Subspaces.

Chong You, Daniel P. Robinson, René Vidal

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

On generalized degrees of freedom with application in linear mixed models selection.

Chong You, Samuel Müller, John T. Ormerod

Stat. Comput., 2016

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit.

Chong You, Daniel P. Robinson, René Vidal

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering.

Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

A divide-and-conquer framework for large-scale subspace clustering.

Chong You, Claire Donnat, Daniel P. Robinson, René Vidal

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Subspace-Sparse Representation.

Chong You, René Vidal

CoRR, 2015

Sparse Subspace Clustering by Orthogonal Matching Pursuit.

Chong You, René Vidal

CoRR, 2015

Geometric Conditions for Subspace-Sparse Recovery.

Chong You, René Vidal

Proceedings of the 32nd International Conference on Machine Learning, 2015