Skip to content
conftrace_

Yudong Chen

53 papers · 2012–2026 · 11 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 13 separate collaboration groups - the largest holds only 45% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Yudong Chen?

8 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Qiaomin Xie, Matthew Zurek, Constantine Caramanis 24 papers · 2013–2026 · COLT, NeurIPS, ICML Hide ▲
Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs COLT 2026 Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL COLT 2025 Stable Offline Value Function Learning with Bisimulation-based Representations ICML 2025 The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis ALT 2025 Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way AISTATS 2025 Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference AAAI 2024 Gap-Free Clustering: Sensitivity and Robustness of SDP COLT 2024 Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces ICML 2024 Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value ICML 2024 Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs NeurIPS 2024 Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024 The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize NeurIPS 2024 Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption NeurIPS 2023 Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning NeurIPS 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 NeurIPS 2020 Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly COLT 2019 Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities NeurIPS 2019 Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression COLT 2019 Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models COLT 2018 Fast Algorithms for Robust PCA via Gradient Descent NeurIPS 2016 A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates COLT 2014 Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery ICML 2013 Robust Sparse Regression under Adversarial Corruption ICML 2013
5 papers whose co-authors appear nowhere else under this name
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration ICML 2025 The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure NeurIPS 2024 Curriculum Disentangled Recommendation with Noisy Multi-feedback NeurIPS 2021 Deep Supervised Hashing With Anchor Graph ICCV 2019 Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization CVPR 2016

Venues · all papers under this name

ICML (15) NeurIPS (14) COLT (8) JMLR (5) ICLR (3) AAAI (2) AISTATS (2) ALT (1) CVPR (1) ICCV (1) WACV (1)