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Chong You

30 papers · 2015–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (46) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (114) ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (30) πŸ”₯ Unstoppable (11) ❓ The Questioner

Conferences

CVPR (7) ICML (7) NIPS (6) ICLR (5) JMLR (2) AISTATS (1) ECCV (1) ICCV (1)

Top co-authors

RenΓ© Vidal (9) Zhihui Zhu (9) Yi Ma (7) Qing Qu (7) Chun-Guang Li (5) Jinxin Zhou (4) Xiao Li (4) Daniel P. Robinson (4) Sanjiv Kumar (4) Yaodong Yu (3)

Keywords

subspace clustering (6) feature learning (4) neural collapse (3) dictionary learning (3) neural network (3) deep neural network (3) sparse representation (3) sparse recovery (3) simplex equiangular tight frame (2) rate reduction (2) representation learning (2) sparse optimization (2) image classification (2) self-expressive model (2) sparse coding (2) self-supervised learning (2) convolutional neural network (2) l1 regularization (2) discriminative representation (2) spectral clustering (1)

Papers

Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models AISTATS 2025
On Bias-Variance Alignment in Deep Models ICLR 2024
Functional Interpolation for Relative Positions improves Long Context Transformers ICLR 2024
Generalized Neural Collapse for a Large Number of Classes ICML 2024
Teacher Guided Training: An Efficient Framework for Knowledge Transfer ICLR 2023
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers ICLR 2023
Revisiting Sparse Convolutional Model for Visual Recognition NIPS 2022
Recovery and Generalization in Over-Realized Dictionary Learning JMLR 2022
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction JMLR 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features ICML 2022
Robust Training under Label Noise by Over-parameterization ICML 2022
Are All Losses Created Equal: A Neural Collapse Perspective NIPS 2022
Learning a Self-Expressive Network for Subspace Clustering CVPR 2021
Incremental Learning via Rate Reduction CVPR 2021
A Critique of Self-Expressive Deep Subspace Clustering ICLR 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features NIPS 2021
A Nullspace Property for Subspace-Preserving Recovery ICML 2021
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training NIPS 2021
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction NIPS 2020
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NIPS 2020
Stochastic Sparse Subspace Clustering CVPR 2020
Deep Isometric Learning for Visual Recognition ICML 2020
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020
Self-Supervised Convolutional Subspace Clustering Network CVPR 2019
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV 2019
Scalable Exemplar-based Subspace Clustering on Class-Imbalanced Data ECCV 2018
Provable Self-Representation Based Outlier Detection in a Union of Subspaces CVPR 2017
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit CVPR 2016
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering CVPR 2016
Geometric Conditions for Subspace-Sparse Recovery ICML 2015