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Yudong Chen

52 papers · 2012–2025 · 11 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer πŸƒ Academic Marathon (13) 🌈 Renaissance Researcher (8) 🌍 Conference Polyglot (11) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (9) πŸ—ΊοΈ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (4) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown πŸ† Keyword Champion (3) πŸ† Grand Slam πŸ”¬ Deep Specialist (14) πŸ”₯ Unstoppable (14) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (191) πŸ’Ž Century Club (52)

Conferences

ICML (15) NIPS (14) COLT (7) JMLR (5) ICLR (3) AAAI (2) AISTATS (2) ALT (1) CVPR (1) ICCV (1) WACV (1)

Top co-authors

Qiaomin Xie (10) Huan Xu (8) Matthew Zurek (5) Constantine Caramanis (5) Xuwei Xu (4) Sujay Sanghavi (4) Shiau Hong Lim (4) Jiajun Liu (4) Yingjie Fei (4) Sen Wang (4)

Keywords

graph clustering (9) stochastic block model (7) convex optimization (7) community detection (5) matrix completion (4) markov chain (4) semidefinite programming (3) regret bound (3) mixture model (3) sample complexity (3) support recovery (2) maximum likelihood (2) non-convex optimization (2) sparse regression (2) nonconvex optimization (2) expectation maximization (2) computational complexity (2) global convergence (2) convergence analysis (2) stochastic optimization (2)

Papers

Medium-Difficulty Samples Constitute Smoothed Decision Boundary for Knowledge Distillation on Pruned Datasets ICLR 2025
RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers ICML 2025
Stable Offline Value Function Learning with Bisimulation-based Representations ICML 2025
Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL COLT 2025
LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently ICML 2025
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration ICML 2025
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks ICLR 2025
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way AISTATS 2025
The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis ALT 2025
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks ICLR 2024
Gap-Free Clustering: Sensitivity and Robustness of SDP COLT 2024
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value ICML 2024
GTP-ViT: Efficient Vision Transformers via Graph-Based Token Propagation WACV 2024
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize NIPS 2024
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs NIPS 2024
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure NIPS 2024
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces ICML 2024
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference AAAI 2024
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption NIPS 2023
Improved Feature Distillation via Projector Ensemble NIPS 2022
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning NIPS 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery NIPS 2021
Curriculum Disentangled Recommendation with Noisy Multi-feedback NIPS 2021
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium COLT 2020
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret NIPS 2020
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling AAAI 2020
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning ICML 2019
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression COLT 2019
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities NIPS 2019
Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly COLT 2019
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery NIPS 2019
Deep Supervised Hashing With Anchor Graph ICCV 2019
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates ICML 2018
Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models COLT 2018
Clustering from General Pairwise Observations with Applications to Time-varying Graphs JMLR 2017
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization CVPR 2016
Fast Algorithms for Robust PCA via Gradient Descent NIPS 2016
Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices JMLR 2016
A Convex Optimization Framework for Bi-Clustering ICML 2015
Completing Any Low-rank Matrix, Provably JMLR 2015
Iterative and Active Graph Clustering Using Trace Norm Minimization Without Cluster Size Constraints JMLR 2015
Clustering from Labels and Time-Varying Graphs NIPS 2014
Weighted Graph Clustering with Non-Uniform Uncertainties ICML 2014
Coherent Matrix Completion ICML 2014
A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates COLT 2014
Clustering Partially Observed Graphs via Convex Optimization JMLR 2014
Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting ICML 2014
Robust Sparse Regression under Adversarial Corruption ICML 2013
Breaking the Small Cluster Barrier of Graph Clustering ICML 2013
Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery ICML 2013
Clustering Sparse Graphs NIPS 2012