Yudong Chen

According to our database, Yudong Chen authored at least 94 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Global Optimality of the EM Algorithm for Mixtures of Two-Component Linear Regressions.

Jeongyeol Kwon, Wei Qian, Yudong Chen, Constantine Caramanis, Damek Davis, Nhat Ho

IEEE Trans. Inf. Theory, September, 2024

Local Minima Structures in Gaussian Mixture Models.

Yudong Chen, Dogyoon Song, Xumei Xi, Yuqian Zhang

IEEE Trans. Inf. Theory, June, 2024

The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure.

Tyler Sam, Yudong Chen, Christina Lee Yu

CoRR, 2024

Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way.

Jeongyeol Kwon, Luke Dotson, Yudong Chen, Qiaomin Xie

CoRR, 2024

Stable Offline Value Function Learning with Bisimulation-based Representations.

Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

CoRR, 2024

Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows.

Yudong Chen, Xumei Xi, Christina Lee Yu

CoRR, 2024

Inception: Efficiently Computable Misinformation Attacks on Markov Games.

Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2024

When is exponential asymptotic optimality achievable in average-reward restless bandits?

Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

CoRR, 2024

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize.

Dongyan Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie

CoRR, 2024

Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits.

Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

CoRR, 2024

Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA.

Yixuan Zhang, Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie

Proceedings of the Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, 2024

Inception: Efficiently Computable Misinformation Attacks on Markov Games.

Jeremy McMahan, Young Wu, Yudong Chen, Jerry Zhu, Qiaomin Xie

RLJ, 2024

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces.

Brahma S. Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements.

Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference.

Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Algorithmic Regularization in Model-Free Overparametrized Asymmetric Matrix Factorization.

Liwei Jiang, Yudong Chen, Lijun Ding

SIAM J. Math. Data Sci., September, 2023

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium.

Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang

Math. Oper. Res., February, 2023

Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure.

Tyler Sam, Yudong Chen, Christina Lee Yu

Proc. ACM Meas. Anal. Comput. Syst., 2023

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2023

VISER: A Tractable Solution Concept for Games with Information Asymmetry.

Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2023

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning.

Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

CoRR, 2023

Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure.

Xumei Xi, Christina Lee Yu, Yudong Chen

CoRR, 2023

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes.

Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie

Proceedings of the Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2023

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption.

Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling.

Xumei Xi, Christina Lee Yu, Yudong Chen

Proceedings of the IEEE International Symposium on Information Theory, 2023

2022

Structures of Spurious Local Minima in k-Means.

Wei Qian, Yuqian Zhang, Yudong Chen

IEEE Trans. Inf. Theory, 2022

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Johan A. K. Suykens

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Hidden Integrality and Semirandom Robustness of SDP Relaxation for Sub-Gaussian Mixture Model.

Yingjie Fei, Yudong Chen

Math. Oper. Res., 2022

2021

Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.

Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy

Found. Comput. Math., 2021

Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning.

Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery.

Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Achieving the Bayes Error Rate in Synchronization and Block Models by SDP, Robustly.

Yingjie Fei, Yudong Chen

IEEE Trans. Inf. Theory, 2020

Leave-One-Out Approach for Matrix Completion: Primal and Dual Analysis.

Lijun Ding, Yudong Chen

IEEE Trans. Inf. Theory, 2020

Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm.

Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Likelihood Landscape and Local Minima Structures of Gaussian Mixture Models.

Yudong Chen, Xumei Xi

CoRR, 2020

Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle.

Lijun Ding, Yuqian Zhang, Yudong Chen

CoRR, 2020

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret.

Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Random Fourier Features via Fast Surrogate Leverage Weighted Sampling.

Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes.

Dong Yin, Ramtin Pedarsani, Yudong Chen, Kannan Ramchandran

IEEE Trans. Inf. Theory, 2019

Exponential Error Rates of SDP for Block Models: Beyond Grothendieck's Inequality.

Yingjie Fei, Yudong Chen

IEEE Trans. Inf. Theory, 2019

Clustering Degree-Corrected Stochastic Block Model with Outliers.

Xin Qian, Yudong Chen, Andreea Minca

CoRR, 2019

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery.

Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning.

Dong Yin, Yudong Chen, Kannan Ramchandran, Peter L. Bartlett

Proceedings of the 36th International Conference on Machine Learning, 2019

Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression.

Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis

Proceedings of the Conference on Learning Theory, 2019

Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly.

Yingjie Fei, Yudong Chen

Proceedings of the Conference on Learning Theory, 2019

2018

Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates.

Yudong Chen, Xinyang Yi, Constantine Caramanis

IEEE Trans. Inf. Theory, 2018

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation: Recent Theory and Fast Algorithms via Convex and Nonconvex Optimization.

Yudong Chen, Yuejie Chi

IEEE Signal Process. Mag., 2018

Convex Relaxation Methods for Community Detection.

Xiaodong Li, Yudong Chen, Jiaming Xu

CoRR, 2018

Hidden Integrality of SDP Relaxation for Sub-Gaussian Mixture Models.

Yingjie Fei, Yudong Chen

CoRR, 2018

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation.

Yudong Chen, Yuejie Chi

CoRR, 2018

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates.

Dong Yin, Yudong Chen, Kannan Ramchandran, Peter L. Bartlett

Proceedings of the 35th International Conference on Machine Learning, 2018

Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models.

Yingjie Fei, Yudong Chen

Proceedings of the Conference On Learning Theory, 2018

2017

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent.

Yudong Chen, Lili Su, Jiaming Xu

Proc. ACM Meas. Anal. Comput. Syst., 2017

Clustering from General Pairwise Observations with Applications to Time-varying Graphs.

Shiau Hong Lim, Yudong Chen, Huan Xu

J. Mach. Learn. Res., 2017

2016

Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs.

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

IEEE Trans. Inf. Theory, 2016

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices.

Yudong Chen, Jiaming Xu

J. Mach. Learn. Res., 2016

Fast Algorithms for Robust PCA via Gradient Descent.

Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization.

Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Incoherence-Optimal Matrix Completion.

Yudong Chen

IEEE Trans. Inf. Theory, 2015

Completing any low-rank matrix, provably.

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward

J. Mach. Learn. Res., 2015

Iterative and active graph clustering using trace norm minimization without cluster size constraints.

Nir Ailon, Yudong Chen, Huan Xu

J. Mach. Learn. Res., 2015

Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees.

Yudong Chen, Martin J. Wainwright

CoRR, 2015

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models.

Yudong Chen, Xiaodong Li, Jiaming Xu

CoRR, 2015

A Convex Optimization Framework for Bi-Clustering.

Shiau Hong Lim, Yudong Chen, Huan Xu

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Improved Graph Clustering.

Yudong Chen, Sujay Sanghavi, Huan Xu

IEEE Trans. Inf. Theory, 2014

Clustering partially observed graphs via convex optimization.

Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu

J. Mach. Learn. Res., 2014

Clustering from Labels and Time-Varying Graphs.

Shiau Hong Lim, Yudong Chen, Huan Xu

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting.

Yudong Chen, Jiaming Xu

Proceedings of the 31th International Conference on Machine Learning, 2014

Weighted Graph Clustering with Non-Uniform Uncertainties.

Yudong Chen, Shiau Hong Lim, Huan Xu

Proceedings of the 31th International Conference on Machine Learning, 2014

Coherent Matrix Completion.

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward

Proceedings of the 31th International Conference on Machine Learning, 2014

A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates.

Yudong Chen, Xinyang Yi, Constantine Caramanis

Proceedings of The 27th Conference on Learning Theory, 2014

2013

User Association for Load Balancing in Heterogeneous Cellular Networks.

Qiaoyang Ye, Beiyu Rong, Yudong Chen, Mazin Al-Shalash, Constantine Caramanis, Jeffrey G. Andrews

IEEE Trans. Wirel. Commun., 2013

Low-Rank Matrix Recovery From Errors and Erasures.

Yudong Chen, Ali Jalali, Sujay Sanghavi, Constantine Caramanis

IEEE Trans. Inf. Theory, 2013

Detecting Overlapping Temporal Community Structure in Time-Evolving Networks

Yudong Chen, Vikas Kawadia, Rahul Urgaonkar

CoRR, 2013

Robust High Dimensional Sparse Regression and Matching Pursuit

Yudong Chen, Constantine Caramanis, Shie Mannor

CoRR, 2013

A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise.

Yudong Chen, Xinyang Yi, Constantine Caramanis

CoRR, 2013

Robust Sparse Regression under Adversarial Corruption.

Yudong Chen, Constantine Caramanis, Shie Mannor

Proceedings of the 30th International Conference on Machine Learning, 2013

Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery.

Yudong Chen, Constantine Caramanis

Proceedings of the 30th International Conference on Machine Learning, 2013

Breaking the Small Cluster Barrier of Graph Clustering.

Nir Ailon, Yudong Chen, Huan Xu

Proceedings of the 30th International Conference on Machine Learning, 2013

Quantization errors of modulo sigma-delta modulated ARMA processes.

Li Li, Yudong Chen

Proceedings of the 2013 IEEE China Summit and International Conference on Signal and Information Processing, 2013

2012

Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results

Yudong Chen, Constantine Caramanis

CoRR, 2012

Simple algorithms for sparse linear regression with uncertain covariates.

Yudong Chen, Constantine Caramanis

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Clustering Sparse Graphs.

Yudong Chen, Sujay Sanghavi, Huan Xu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Towards an optimal user association in heterogeneous cellular networks.

Qiaoyang Ye, Beiyu Rong, Yudong Chen, Constantine Caramanis, Jeffrey G. Andrews

Proceedings of the 2012 IEEE Global Communications Conference, 2012

A Mixed-Fractal Traffic Flow Model Whose Hurst Exponent Appears Crossover.

Li Li, Zhiheng Li, Yi Zhang, Yudong Chen

Proceedings of the Fifth International Joint Conference on Computational Sciences and Optimization, 2012

2011

Robust Matrix Completion with Corrupted Columns

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

CoRR, 2011

Robust Matrix Completion and Corrupted Columns.

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 28th International Conference on Machine Learning, 2011

2009

PCA based Hurst exponent estimator for fBm signals under disturbances.

Li Li, Jianming Hu, Yudong Chen, Yi Zhang

IEEE Trans. Signal Process., 2009

Quantization Errors of Uniformly Quantized fGn and fBm Signals.

Zhiheng Li, Yudong Chen, Li Li, Yi Zhang

IEEE Signal Process. Lett., 2009

A Mixed-Fractal Model for Network Traffic

Li Li, Yudong Chen, Yi Zhang

CoRR, 2009

Quantization Errors of fGn and fBm Signals

Zhiheng Li, Li Li, Yudong Chen, Yi Zhang

CoRR, 2009

2006

Pattern Discovering of Regional Traffic Status with Self-Organizing Maps.

Yudong Chen, Yi Zhang, Jianming Hu, Danya Yao

Proceedings of the IEEE Intelligent Transportation Systems Conference, 2006