Yudong Chen

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