Yudong Chen

Orcid: 0000-0002-6416-5635

Affiliations:
  • University of Wisconsin-Madison, Madison, WI, USA
  • Cornell University, School of Operations Research and Information Engineering, Ithaca, NY, USA
  • University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA
  • University of Texas at Austin, Department of Electrical and Computer Engineering, TX, USA


According to our database1, Yudong Chen authored at least 80 papers between 2009 and 2024.

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Bibliography

2024
Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits.
CoRR, 2024

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Algorithmic Regularization in Model-Free Overparametrized Asymmetric Matrix Factorization.
SIAM J. Math. Data Sci., September, 2023

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium.
Math. Oper. Res., February, 2023

Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure.
Proc. ACM Meas. Anal. Comput. Syst., 2023

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.
CoRR, 2023

VISER: A Tractable Solution Concept for Games with Information Asymmetry.
CoRR, 2023

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements.
CoRR, 2023

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning.
CoRR, 2023

Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure.
CoRR, 2023

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes.
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.
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.
Proceedings of the IEEE International Symposium on Information Theory, 2023

2022
Structures of Spurious Local Minima in k-Means.
IEEE Trans. Inf. Theory, 2022

Towards a Unified Quadrature Framework for Large-Scale Kernel Machines.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Hidden Integrality and Semirandom Robustness of SDP Relaxation for Sub-Gaussian Mixture Model.
Math. Oper. Res., 2022

2021
Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.
Found. Comput. Math., 2021

Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning.
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.
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.
IEEE Trans. Inf. Theory, 2020

Leave-One-Out Approach for Matrix Completion: Primal and Dual Analysis.
IEEE Trans. Inf. Theory, 2020

Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Likelihood Landscape and Local Minima Structures of Gaussian Mixture Models.
CoRR, 2020

Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle.
CoRR, 2020

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes.
IEEE Trans. Inf. Theory, 2019

Exponential Error Rates of SDP for Block Models: Beyond Grothendieck's Inequality.
IEEE Trans. Inf. Theory, 2019

Clustering Degree-Corrected Stochastic Block Model with Outliers.
CoRR, 2019

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression.
Proceedings of the Conference on Learning Theory, 2019

Achieving the Bayes Error Rate in Stochastic Block Model by SDP, Robustly.
Proceedings of the Conference on Learning Theory, 2019

2018
Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates.
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.
IEEE Signal Process. Mag., 2018

Convex Relaxation Methods for Community Detection.
CoRR, 2018

Hidden Integrality of SDP Relaxation for Sub-Gaussian Mixture Models.
CoRR, 2018

Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation.
CoRR, 2018

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates.
Proceedings of the 35th International Conference on Machine Learning, 2018

Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models.
Proceedings of the Conference On Learning Theory, 2018

2017
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent.
Proc. ACM Meas. Anal. Comput. Syst., 2017

Clustering from General Pairwise Observations with Applications to Time-varying Graphs.
J. Mach. Learn. Res., 2017

2016
Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs.
IEEE Trans. Inf. Theory, 2016

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices.
J. Mach. Learn. Res., 2016

Fast Algorithms for Robust PCA via Gradient Descent.
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.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Incoherence-Optimal Matrix Completion.
IEEE Trans. Inf. Theory, 2015

Completing any low-rank matrix, provably.
J. Mach. Learn. Res., 2015

Iterative and active graph clustering using trace norm minimization without cluster size constraints.
J. Mach. Learn. Res., 2015

Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees.
CoRR, 2015

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models.
CoRR, 2015

A Convex Optimization Framework for Bi-Clustering.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Improved Graph Clustering.
IEEE Trans. Inf. Theory, 2014

Clustering partially observed graphs via convex optimization.
J. Mach. Learn. Res., 2014

Clustering from Labels and Time-Varying Graphs.
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.
Proceedings of the 31th International Conference on Machine Learning, 2014

Weighted Graph Clustering with Non-Uniform Uncertainties.
Proceedings of the 31th International Conference on Machine Learning, 2014

Coherent Matrix Completion.
Proceedings of the 31th International Conference on Machine Learning, 2014

A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
User Association for Load Balancing in Heterogeneous Cellular Networks.
IEEE Trans. Wirel. Commun., 2013

Low-Rank Matrix Recovery From Errors and Erasures.
IEEE Trans. Inf. Theory, 2013

Detecting Overlapping Temporal Community Structure in Time-Evolving Networks
CoRR, 2013

Robust High Dimensional Sparse Regression and Matching Pursuit
CoRR, 2013

A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise.
CoRR, 2013

Robust Sparse Regression under Adversarial Corruption.
Proceedings of the 30th International Conference on Machine Learning, 2013

Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery.
Proceedings of the 30th International Conference on Machine Learning, 2013

Breaking the Small Cluster Barrier of Graph Clustering.
Proceedings of the 30th International Conference on Machine Learning, 2013

Quantization errors of modulo sigma-delta modulated ARMA processes.
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
CoRR, 2012

Simple algorithms for sparse linear regression with uncertain covariates.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Clustering Sparse Graphs.
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.
Proceedings of the 2012 IEEE Global Communications Conference, 2012

A Mixed-Fractal Traffic Flow Model Whose Hurst Exponent Appears Crossover.
Proceedings of the Fifth International Joint Conference on Computational Sciences and Optimization, 2012

2011
Robust Matrix Completion with Corrupted Columns
CoRR, 2011

Robust Matrix Completion and Corrupted Columns.
Proceedings of the 28th International Conference on Machine Learning, 2011

2009
PCA based Hurst exponent estimator for fBm signals under disturbances.
IEEE Trans. Signal Process., 2009

Quantization Errors of Uniformly Quantized fGn and fBm Signals.
IEEE Signal Process. Lett., 2009

A Mixed-Fractal Model for Network Traffic
CoRR, 2009

Quantization Errors of fGn and fBm Signals
CoRR, 2009


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