Pattern Discovering of Regional Traffic Status with Self-Organizing Maps. - Yudong Chen 001; Yi Zhang 029; Jianming Hu; Danya Yao (ITSC, 2006)

Quantization Errors of fGn and fBm Signals - Zhiheng Li 001; Li Li 013; Yudong Chen 001; Yi Zhang 029 (CoRR, 2009)

A Mixed-Fractal Model for Network Traffic - Li Li 013; Yudong Chen 001; Yi Zhang 029 (CoRR, 2009)

Quantization Errors of Uniformly Quantized fGn and fBm Signals. - Zhiheng Li 001; Yudong Chen 001; Li Li 013; Yi Zhang 029 (IEEE Signal Process. Lett., 2009)

PCA based Hurst exponent estimator for fBm signals under disturbances. - Li Li 013; Jianming Hu; Yudong Chen 001; Yi Zhang 029 (IEEE Trans. Signal Process., 2009)

Robust Matrix Completion and Corrupted Columns. - Yudong Chen 001; Huan Xu 001; Constantine Caramanis; Sujay Sanghavi (ICML, 2011)

Robust Matrix Completion with Corrupted Columns - Yudong Chen 001; Huan Xu 001; Constantine Caramanis; Sujay Sanghavi (CoRR, 2011)

A Mixed-Fractal Traffic Flow Model Whose Hurst Exponent Appears Crossover. - Li Li 013; Zhiheng Li 001; Yi Zhang 029; Yudong Chen 001 (CSO, 2012)

Towards an optimal user association in heterogeneous cellular networks. - Qiaoyang Ye; Beiyu Rong; Yudong Chen 001; Constantine Caramanis; Jeffrey G. Andrews (GLOBECOM, 2012)

Clustering Sparse Graphs. - Yudong Chen 001; Sujay Sanghavi; Huan Xu 001 (NIPS, 2012)

Simple algorithms for sparse linear regression with uncertain covariates. - Yudong Chen 001; Constantine Caramanis (SSP, 2012)

Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results - Yudong Chen 001; Constantine Caramanis (CoRR, 2012)

Quantization errors of modulo sigma-delta modulated ARMA processes. - Li Li 013; Yudong Chen 001 (ChinaSIP, 2013)

Breaking the Small Cluster Barrier of Graph Clustering. - Nir Ailon; Yudong Chen 001; Huan Xu 001 (ICML (3), 2013)

Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery. - Yudong Chen 001; Constantine Caramanis (ICML (1), 2013)

Robust Sparse Regression under Adversarial Corruption. - Yudong Chen 001; Constantine Caramanis; Shie Mannor (ICML (3), 2013)

A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise. - Yudong Chen 001; Xinyang Yi; Constantine Caramanis (CoRR, 2013)

Robust High Dimensional Sparse Regression and Matching Pursuit - Yudong Chen 001; Constantine Caramanis; Shie Mannor (CoRR, 2013)

Detecting Overlapping Temporal Community Structure in Time-Evolving Networks - Yudong Chen 001; Vikas Kawadia; Rahul Urgaonkar (CoRR, 2013)

Low-Rank Matrix Recovery From Errors and Erasures. - Yudong Chen 001; Ali Jalali; Sujay Sanghavi; Constantine Caramanis (IEEE Trans. Inf. Theory, 2013)

User Association for Load Balancing in Heterogeneous Cellular Networks. - Qiaoyang Ye; Beiyu Rong; Yudong Chen 001; Mazin Al-Shalash; Constantine Caramanis; Jeffrey G. Andrews (IEEE Trans. Wirel. Commun., 2013)

A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates. - Yudong Chen 001; Xinyang Yi; Constantine Caramanis (COLT, 2014)

Coherent Matrix Completion. - Yudong Chen 001; Srinadh Bhojanapalli; Sujay Sanghavi; Rachel A. Ward (ICML, 2014)

Weighted Graph Clustering with Non-Uniform Uncertainties. - Yudong Chen 001; Shiau Hong Lim; Huan Xu 001 (ICML, 2014)

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting. - Yudong Chen 001; Jiaming Xu 002 (ICML, 2014)

Clustering from Labels and Time-Varying Graphs. - Shiau Hong Lim; Yudong Chen 001; Huan Xu 001 (NIPS, 2014)

Clustering partially observed graphs via convex optimization. - Yudong Chen 001; Ali Jalali; Sujay Sanghavi; Huan Xu 001 (J. Mach. Learn. Res., 2014)

Improved Graph Clustering. - Yudong Chen 001; Sujay Sanghavi; Huan Xu 001 (IEEE Trans. Inf. Theory, 2014)

A Convex Optimization Framework for Bi-Clustering. - Shiau Hong Lim; Yudong Chen 001; Huan Xu 001 (ICML, 2015)

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models. - Yudong Chen 001; Xiaodong Li; Jiaming Xu 002 (CoRR, 2015)

Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees. - Yudong Chen 001; Martin J. Wainwright (CoRR, 2015)

Iterative and active graph clustering using trace norm minimization without cluster size constraints. - Nir Ailon; Yudong Chen 001; Huan Xu 001 (J. Mach. Learn. Res., 2015)

Completing any low-rank matrix, provably. - Yudong Chen 001; Srinadh Bhojanapalli; Sujay Sanghavi; Rachel A. Ward (J. Mach. Learn. Res., 2015)

Incoherence-Optimal Matrix Completion. - Yudong Chen 001 (IEEE Trans. Inf. Theory, 2015)

Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization. - Canyi Lu; Jiashi Feng; Yudong Chen 001; Wei Liu 005; Zhouchen Lin; Shuicheng Yan (CVPR, 2016)

Fast Algorithms for Robust PCA via Gradient Descent. - Xinyang Yi; Dohyung Park; Yudong Chen 001; Constantine Caramanis (NIPS, 2016)

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices. - Yudong Chen 001; Jiaming Xu 002 (J. Mach. Learn. Res., 2016)

Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs. - Yudong Chen 001; Huan Xu 001; Constantine Caramanis; Sujay Sanghavi (IEEE Trans. Inf. Theory, 2016)

Clustering from General Pairwise Observations with Applications to Time-varying Graphs. - Shiau Hong Lim; Yudong Chen 001; Huan Xu 001 (J. Mach. Learn. Res., 2017)

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. - Yudong Chen 001; Lili Su; Jiaming Xu 002 (Proc. ACM Meas. Anal. Comput. Syst., 2017)

Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models. - Yingjie Fei; Yudong Chen 001 (COLT, 2018)

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates. - Dong Yin; Yudong Chen 001; Kannan Ramchandran; Peter L. Bartlett (ICML, 2018)

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation. - Yudong Chen 001; Yuejie Chi (CoRR, 2018)

Hidden Integrality of SDP Relaxation for Sub-Gaussian Mixture Models. - Yingjie Fei; Yudong Chen 001 (CoRR, 2018)

Convex Relaxation Methods for Community Detection. - Xiaodong Li; Yudong Chen 001; Jiaming Xu 002 (CoRR, 2018)

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation: Recent Theory and Fast Algorithms via Convex and Nonconvex Optimization. - Yudong Chen 001; Yuejie Chi (IEEE Signal Process. Mag., 2018)

Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates. - Yudong Chen 001; Xinyang Yi; Constantine Caramanis (IEEE Trans. Inf. Theory, 2018)

Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly. - Yingjie Fei; Yudong Chen 001 (COLT, 2019)

Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression. - Jeongyeol Kwon; Wei Qian; Constantine Caramanis; Yudong Chen 001; Damek Davis (COLT, 2019)

Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning. - Dong Yin; Yudong Chen 001; Kannan Ramchandran; Peter L. Bartlett (ICML, 2019)

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery. - Jicong Fan 001; Lijun Ding; Yudong Chen 001; Madeleine Udell (NeurIPS, 2019)

Clustering Degree-Corrected Stochastic Block Model with Outliers. - Xin Qian; Yudong Chen 001; Andreea Minca (CoRR, 2019)

Exponential Error Rates of SDP for Block Models: Beyond Grothendieck's Inequality. - Yingjie Fei; Yudong Chen 001 (IEEE Trans. Inf. Theory, 2019)

Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes. - Dong Yin; Ramtin Pedarsani; Yudong Chen 001; Kannan Ramchandran (IEEE Trans. Inf. Theory, 2019)

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling. - Fanghui Liu 001; Xiaolin Huang; Yudong Chen 001; Jie Yang 002; Johan A. K. Suykens (AAAI, 2020)

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. - Yingjie Fei; Zhuoran Yang; Yudong Chen 001; Zhaoran Wang 001; Qiaomin Xie (NeurIPS, 2020)

Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle. - Lijun Ding; Yuqian Zhang; Yudong Chen 001 (CoRR, 2020)

Likelihood Landscape and Local Minima Structures of Gaussian Mixture Models. - Yudong Chen 001; Xumei Xi (CoRR, 2020)

Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm. - Canyi Lu; Jiashi Feng; Yudong Chen 001; Wei Liu 005; Zhouchen Lin; Shuicheng Yan (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Leave-One-Out Approach for Matrix Completion: Primal and Dual Analysis. - Lijun Ding; Yudong Chen 001 (IEEE Trans. Inf. Theory, 2020)

Achieving the Bayes Error Rate in Synchronization and Block Models by SDP, Robustly. - Yingjie Fei; Yudong Chen 001 (IEEE Trans. Inf. Theory, 2020)

Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. - Lijun Ding; Liwei Jiang; Yudong Chen 001; Qing Qu 001; Zhihui Zhu (NeurIPS, 2021)

Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. - Yingjie Fei; Zhuoran Yang; Yudong Chen 001; Zhaoran Wang 001 (NeurIPS, 2021)

Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence. - Vasileios Charisopoulos; Yudong Chen 001; Damek Davis; Mateo Díaz; Lijun Ding; Dmitriy Drusvyatskiy (Found. Comput. Math., 2021)

Hidden Integrality and Semirandom Robustness of SDP Relaxation for Sub-Gaussian Mixture Model. - Yingjie Fei; Yudong Chen 001 (Math. Oper. Res., 2022)

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond. - Fanghui Liu 001; Xiaolin Huang; Yudong Chen 001; Johan A. K. Suykens (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines. - Fanghui Liu 001; Xiaolin Huang; Yudong Chen 001; Johan A. K. Suykens (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Structures of Spurious Local Minima in k-Means. - Wei Qian; Yuqian Zhang; Yudong Chen 001 (IEEE Trans. Inf. Theory, 2022)

Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling. - Xumei Xi; Christina Lee Yu; Yudong Chen 001 (ISIT, 2023)

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption. - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (NeurIPS, 2023)

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. - Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS (Abstracts), 2023)

Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure. - Xumei Xi; Christina Lee Yu; Yudong Chen 001 (CoRR, 2023)

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning. - Brahma S. Pavse; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (CoRR, 2023)

VISER: A Tractable Solution Concept for Games with Information Asymmetry. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2023)

Clustering Without an Eigengap. - Matthew Zurek; Yudong Chen 001 (CoRR, 2023)

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. - Young Wu; Jeremy McMahan; Yiding Chen; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2023)

Span-Based Optimal Sample Complexity for Average Reward MDPs. - Matthew Zurek; Yudong Chen 001 (CoRR, 2023)

Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure. - Tyler Sam; Yudong Chen 001; Christina Lee Yu (Proc. ACM Meas. Anal. Comput. Syst., 2023)

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. - Qiaomin Xie; Yudong Chen 001; Zhaoran Wang 001; Zhuoran Yang (Math. Oper. Res., 2023)

Algorithmic Regularization in Model-Free Overparametrized Asymmetric Matrix Factorization. - Liwei Jiang; Yudong Chen 001; Lijun Ding (SIAM J. Math. Data Sci., 2023)

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference. - Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (AAAI, 2024)

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. - Emmanouil-Vasileios Vlatakis-Gkaragkounis; Angeliki Giannou; Yudong Chen 001; Qiaomin Xie (AISTATS, 2024)

Gap-Free Clustering: Sensitivity and Robustness of SDP. - Matthew Zurek; Yudong Chen 001 (COLT, 2024)

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces. - Brahma S. Pavse; Matthew Zurek; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (ICML, 2024)

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. - Young Wu; Jeremy McMahan; Yiding Chen; Yudong Chen 001; Jerry Zhu; Qiaomin Xie (ICML, 2024)

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize. - Dongyan Lucy Huo; Yixuan Zhang; Yudong Chen 001; Qiaomin Xie (NeurIPS, 2024)

The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure. - Tyler Sam; Yudong Chen 001; Christina Lee Yu (NeurIPS, 2024)

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs. - Matthew Zurek; Yudong Chen 001 (NeurIPS, 2024)

Inception: Efficiently Computable Misinformation Attacks on Markov Games. - Jeremy McMahan; Young Wu; Yudong Chen 001; Jerry Zhu; Qiaomin Xie (RLJ, 2024)

Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA. - Yixuan Zhang; Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS/Performance (Abstracts), 2024)

Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits. - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (CoRR, 2024)

When is exponential asymptotic optimality achievable in average-reward restless bandits? - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (CoRR, 2024)

Inception: Efficiently Computable Misinformation Attacks on Markov Games. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2024)

Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows. - Yudong Chen 001; Xumei Xi; Christina Lee Yu (CoRR, 2024)

Stable Offline Value Function Learning with Bisimulation-based Representations. - Brahma S. Pavse; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (CoRR, 2024)

Local Minima Structures in Gaussian Mixture Models. - Yudong Chen 001; Dogyoon Song; Xumei Xi; Yuqian Zhang (IEEE Trans. Inf. Theory, 2024)

Global Optimality of the EM Algorithm for Mixtures of Two-Component Linear Regressions. - Jeongyeol Kwon; Wei Qian; Yudong Chen 001; Constantine Caramanis; Damek Davis; Nhat Ho (IEEE Trans. Inf. Theory, 2024)

Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way. - Jeongyeol Kwon; Luke Dotson; Yudong Chen 001; Qiaomin Xie (AISTATS, 2025)

The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis. - Matthew Zurek; Yudong Chen 001 (ALT, 2025)

Entry-Specific Matrix Estimation Under Arbitrary Sampling Patterns Through the Lens of Network Flows (Extended Abstract). - Yudong Chen 001; Xumei Xi; Christina Lee Yu (ITCS, 2025)

A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression. - Yixuan Zhang; Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS (Abstracts), 2025)

One-step full gradient suffices for low-rank fine-tuning, provably and efficiently. - Yuanhe Zhang; Fanghui Liu 001; Yudong Chen 001 (CoRR, 2025)

Re-examining Double Descent and Scaling Laws under Norm-based Capacity via Deterministic Equivalence. - Yichen Wang; Yudong Chen 001; Lorenzo Rosasco; Fanghui Liu 001 (CoRR, 2025)

Optimally Installing Strict Equilibria. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2025)