Estimating Shared Subspace with AJIVE: The Power and Limitation of Multiple Data Matrices Y. Yang, C. Ma [Slides]
Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation B. Zhao, C. Ma, M. Kolar
Distributionally Robust Risk Evaluation with an Isotonic Constraint Y. Gui, R. F. Barber, C. Ma
Off-Policy Estimation with Adaptively Collected Data: The Power of Online Learning J. Lee, C. Ma Neurips, 2024
Random Pairing MLE for Estimation of Item Parameters in Rasch Model Y. Yang, C. Ma
Batched Nonparametric Contextual Bandits R. Jiang, C. Ma To appear on IEEE Transactions on Information Theory, 2025 [Slides]
Top-\(K\) Ranking with a Monotone Adversary Y. Yang, A. Chen, L. Orecchia, C. Ma COLT, 2024 [Slides] [Code]
On the Design-Dependent Suboptimality of the Lasso R. Pathak, C. Ma [Code]
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift J. Ge, S. Tang, J. Fan, C. Ma, C. Jin ICLR, 2024
Conformalized Matrix Completion Y. Gui, R. F. Barber, C. Ma NeurIPS, 2023 [Code]
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing X. Xu, Y. Shen, Y. Chi, C. Ma ICML, 2023 [Slides]
High-Probability Sample Complexities for Policy Evaluation with Linear Function Approximation G. Li, W. Wu, Y. Chi, C. Ma, A. Rinaldo, Y. Wei IEEE Transactions on Information Theory, 2024
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage Y. Gui, C. Ma, Y. Zhong
Optimally Tackling Covariate Shift in RKHS-Based Nonparametric Regression C. Ma, R. Pathak, M. J. Wainwright Annals of Statistics, 2023 [Slides]
Optimal Tuning-Free Convex Relaxation for Noisy Matrix Completion Y. Yang, C. Ma IEEE Transactions on Information Theory, 2023
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent H. Dong, T. Tong, C. Ma, Y. Chi Information and Inference: A Journal of the IMA, 2023
A New Similarity Measure for Covariate Shift with Applications to Nonparametric Regression R. Pathak, C. Ma, M. J. Wainwright (RP and CM contributed equally) ICML, 2022 (long presentation)
Jump-Start Reinforcement Learning I. Uchendu, T. Xiao, Y. Lu, B. Zhu, M. Yan, J. Simon, M. Bennice, C. Fu, C. Ma, J. Jiao, S Levine, K Hausman ICML, 2023
\(O(1/T)\) Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games Y. Yang, C. Ma ICLR, 2023
Pessimism for Offline Linear Contextual Bandits using \(\ell_{p}\) Confidence Sets G. Li, C. Ma, N. Srebro (alphabetical order) NeurIPS, 2022 [Poster]
Minimax Off-Policy Evaluation for Multi-Armed Bandits C. Ma, B. Zhu, J. Jiao, M. J. Wainwright IEEE Transactions on Information Theory, 2022 [Slides]
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism P. Rashidinejad, B. Zhu, C. Ma, J. Jiao, S. Russell IEEE Transactions on Information Theory, 2022 accepted in part to NeurIPS 2021 [Slides]
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements T. Tong, C. Ma, A. Prater-Bennette, E. Tripp, Y. Chi Journal of Machine Learning Research, 2022 accepted in part to AISTATS, 2022
Spectral Methods for Data Science: A Statistical Perspective Y. Chen, Y. Chi, J. Fan, C. Ma (alphabetical order) Foundations and Trends® in Machine Learning, 2021
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Y. Chen, J. Fan, C. Ma, Y. Yan (alphabetical order) Annals of Statistics, 2021
Learning Mixtures of Low-Rank Models Y. Chen, C. Ma, H. V. Poor, Y. Chen IEEE Transactions on Information Theory, 2021
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number T. Tong, C. Ma, Y. Chi IEEE Transactions on Signal Processing, 2021
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent T. Tong, C. Ma, Y. Chi Journal of Machine Learning Research, 2021
Inference and Uncertainty Quantification for Noisy Matrix Completion Y. Chen, J. Fan, C. Ma, Y. Yan (alphabetical order) Proceedings of the National Academy of Sciences, 2019 [Slides]
A Selective Overview of Deep Learning J. Fan, C. Ma, Y. Zhong (alphabetical order) Statistical Science, 2020
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization Y. Chen, Y. Chi, J. Fan, C. Ma, Y. Yan (alphabetical order) SIAM Journal on Optimization, 2020 [Slides]
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing C. Ma, Y. Li, Y. Chi IEEE Transactions on Signal Processing, 2021 accepted in part to Asilomar 2019
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval Y. Chen, Y. Chi, J. Fan, C. Ma (alphabetical order) Mathematical Programming, 2019 [Slides]
Nonconvex Matrix Factorization from Rank-One Measurements Y. Li, C. Ma, Y. Chen, Y. Chi IEEE Transactions on Information Theory, 2020 accepted in part to AISTATS, 2019
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution C. Ma, K. Wang, Y. Chi, Y. Chen Foundations of Computational Mathematics, 2020 accepted in part to ICML 2018 [Slides]
Spectral Method and Regularized MLE Are Both Optimal for Top-\(K\) Ranking Y. Chen, J. Fan, C. Ma, K. Wang (alphabetical order) Annals of Statistics, 2019 [Slides]
Inter-Subject Analysis: A Partial Gaussian Graphical Model Approach C. Ma, J. Lu, H. Liu Journal of the American Statistical Association, 2020 [Slides]
Fast and Flexible Top-\(K\) Similarity Search on Large Networks J. Zhang, J. Tang, C. Ma, H. Tong, Y. Jing, J. Li, W. Luyten, M. Moens ACM Transactions on Information Systems, 2017 accepted in part to KDD, 2015