Yuxin Chen
Orcid: 0000-0001-9256-5815Affiliations:
- University of Pennsylvania, Wharton School, Philadelphia, PA, USA
- Princeton University, Department of Electrical Engineering, NJ, USA (former)
- Stanford University, Department of Statistics, CA, USA (former)
According to our database1,
Yuxin Chen
authored at least 84 papers
between 2010 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
2023
IEEE Trans. Inf. Theory, November, 2023
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence.
SIAM J. Optim., June, 2023
Uncertainty Quantification for Nonconvex Tensor Completion: Confidence Intervals, Heteroscedasticity and Optimality.
IEEE Trans. Inf. Theory, 2023
Math. Program., 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2022
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction.
IEEE Trans. Inf. Theory, 2022
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization.
Oper. Res., 2022
CoRR, 2022
Model-Based Reinforcement Learning Is Minimax-Optimal for Offline Zero-Sum Markov Games.
CoRR, 2022
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity.
Proceedings of the International Conference on Machine Learning, 2022
MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation.
Proceedings of the IEEE International Conference on Data Mining, 2022
2021
IEEE Trans. Inf. Theory, 2021
Tackling Small Eigen-Gaps: Fine-Grained Eigenvector Estimation and Inference Under Heteroscedastic Noise.
IEEE Trans. Inf. Theory, 2021
Found. Trends Mach. Learn., 2021
Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen-Gaps.
CoRR, 2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Conference on Learning Theory, 2021
2020
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization.
SIAM J. Optim., 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction.
J. Mach. Learn. Res., 2020
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution.
Found. Comput. Math., 2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution.
CoRR, 2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data.
CoRR, 2020
Inference for linear forms of eigenvectors under minimal eigenvalue separation: Asymmetry and heteroscedasticity.
CoRR, 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
IEEE Trans. Signal Process., 2019
Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval.
Math. Program., 2019
Subspace Estimation from Unbalanced and Incomplete Data Matrices: 𝓁<sub>2, ∞</sub> Statistical Guarantees.
CoRR, 2019
CoRR, 2019
2018
Asymmetry Helps: Eigenvalue and Eigenvector Analyses of Asymmetrically Perturbed Low-Rank Matrices.
CoRR, 2018
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
IEEE Trans. Inf. Theory, 2017
The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square.
CoRR, 2017
2016
The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences.
CoRR, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
IEEE Trans. Signal Process., 2015
Backing Off From Infinity: Performance Bounds via Concentration of Spectral Measure for Random MIMO Channels.
IEEE Trans. Inf. Theory, 2015
Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming.
IEEE Trans. Inf. Theory, 2015
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 2015 IEEE Information Theory Workshop, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
IEEE Trans. Inf. Theory, 2014
IEEE Trans. Inf. Theory, 2014
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Robust and universal covariance estimation from quadratic measurements via convex programming.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the IEEE International Conference on Acoustics, 2014
Estimation of simultaneously structured covariance matrices from quadratic measurements.
Proceedings of the IEEE International Conference on Acoustics, 2014
2013
IEEE Trans. Inf. Theory, 2013
Backing off from Infinity: Tight Performance Bounds for Large Random Vector Channels.
CoRR, 2013
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
Proceedings of the 2013 Asilomar Conference on Signals, 2013
2012
IEEE Trans. Inf. Theory, 2012
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
2011
Proceedings of the 2011 IEEE Information Theory Workshop, 2011
Proceedings of the INFOCOM 2011. 30th IEEE International Conference on Computer Communications, 2011
Proceedings of the IEEE International Conference on Acoustics, 2011
Proceedings of the 49th Annual Allerton Conference on Communication, 2011
2010
CoRR, 2010
Proceedings of the IEEE International Symposium on Information Theory, 2010