Chong You

Orcid: 0000-0001-7821-2378

According to our database1, Chong You authored at least 48 papers between 2015 and 2024.

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Bibliography

2024
HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference.
CoRR, 2024

Generalized Neural Collapse for a Large Number of Classes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Functional Interpolation for Relative Positions improves Long Context Transformers.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Bias-Variance Alignment in Deep Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression.
J. Comput. Graph. Stat., 2023

It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models.
CoRR, 2023

Teacher Guided Training: An Efficient Framework for Knowledge Transfer.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Integration of Computer Virtual Reality Technology to College Physical Education.
J. Web Eng., 2022

Recovery and Generalization in Over-Realized Dictionary Learning.
J. Mach. Learn. Res., 2022

ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction.
J. Mach. Learn. Res., 2022

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

Are All Losses Created Equal: A Neural Collapse Perspective.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

Robust Training under Label Noise by Over-parameterization.
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.
Medical Image Anal., 2021

A Geometric Analysis of Neural Collapse with Unconstrained Features.
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.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Critique of Self-Expressive Deep Subspace Clustering.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning a Self-Expressive Network for Subspace Clustering.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Incremental Learning via Rate Reduction.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Analysis of the Relationship between Scintillation Parameters, Multipath and ROTI.
Sensors, 2020

Deep Networks from the Principle of Rate Reduction.
CoRR, 2020

Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction.
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.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Isometric Learning for Visual Recognition.
Proceedings of the 37th International Conference on Machine Learning, 2020

Spatial Analysis of the Correlation between Scintillation Parameters and MP&ROTI.
Proceedings of the European Navigation Conference, 2020

Stochastic Sparse Subspace Clustering.
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.
CoRR, 2019

Classifying and Comparing Approaches to Subspace Clustering with Missing Data.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Is an Affine Constraint Needed for Affine Subspace Clustering?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Self-Supervised Convolutional Subspace Clustering Network.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
On Geometric Analysis of Affine Sparse Subspace Clustering.
IEEE J. Sel. Top. Signal Process., 2018

A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis.
Comput. Optim. Appl., 2018

A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework.
IEEE Trans. Image Process., 2017

Provable Self-Representation Based Outlier Detection in a Union of Subspaces.
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.
Stat. Comput., 2016

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

A divide-and-conquer framework for large-scale subspace clustering.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Subspace-Sparse Representation.
CoRR, 2015

Sparse Subspace Clustering by Orthogonal Matching Pursuit.
CoRR, 2015

Geometric Conditions for Subspace-Sparse Recovery.
Proceedings of the 32nd International Conference on Machine Learning, 2015


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