Panther: Fast Top-k Similarity Search on Large Networks. - Jing Zhang 001; Jie Tang 001; Cong Ma 001; Hanghang Tong; Yu Jing; Juanzi Li (KDD, 2015)

Spectral Method and Regularized MLE Are Both Optimal for Top-$K$ Ranking. - Yuxin Chen 002; Jianqing Fan; Cong Ma 001; Kaizheng Wang (CoRR, 2017)

Fast and Flexible Top-k Similarity Search on Large Networks. - Jing Zhang 001; Jie Tang 001; Cong Ma 001; Hanghang Tong; Yu Jing; Juanzi Li; Walter Luyten; Marie-Francine Moens (ACM Trans. Inf. Syst., 2017)

Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion. - Cong Ma 001; Kaizheng Wang; Yuejie Chi; Yuxin Chen 002 (ICML, 2018)

A Selective Overview of Deep Learning. - Jianqing Fan; Cong Ma 001; Yiqiao Zhong (CoRR, 2019)

Inference and Uncertainty Quantification for Noisy Matrix Completion. - Yuxin Chen 002; Jianqing Fan; Cong Ma 001; Yuling Yan (CoRR, 2019)

Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval. - Yuxin Chen 002; Yuejie Chi; Jianqing Fan; Cong Ma 001 (Math. Program., 2019)

Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data. - Yuxin Chen 002; Jianqing Fan; Cong Ma 001; Yuling Yan (CoRR, 2020)

Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution. - Cong Ma 001; Kaizheng Wang; Yuejie Chi; Yuxin Chen 002 (Found. Comput. Math., 2020)

Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization. - Yuxin Chen 002; Yuejie Chi; Jianqing Fan; Cong Ma 001; Yuling Yan (SIAM J. Optim., 2020)

Spectral Methods for Data Science: A Statistical Perspective. - Yuxin Chen 002; Yuejie Chi; Jianqing Fan; Cong Ma 001 (Found. Trends Mach. Learn., 2021)

Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent. - Tian Tong; Cong Ma 001; Yuejie Chi (J. Mach. Learn. Res., 2021)

Learning Mixtures of Low-Rank Models. - Yanxi Chen 001; Cong Ma 001; H. Vincent Poor; Yuxin Chen 002 (IEEE Trans. Inf. Theory, 2021)

Nonconvex Matrix Factorization From Rank-One Measurements. - Yuanxin Li 003; Cong Ma 001; Yuxin Chen 002; Yuejie Chi (IEEE Trans. Inf. Theory, 2021)

Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing. - Cong Ma 001; Yuanxin Li 003; Yuejie Chi (IEEE Trans. Signal Process., 2021)

Low-Rank Matrix Recovery With Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number. - Tian Tong; Cong Ma 001; Yuejie Chi (IEEE Trans. Signal Process., 2021)

Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion. - Tian Tong; Cong Ma 001; Ashley Prater-Bennette; Erin E. Tripp; Yuejie Chi (AISTATS, 2022)

Accelerating ILL-Conditioned Robust Low-Rank Tensor Regression. - Tian Tong; Cong Ma 001; Yuejie Chi (ICASSP, 2022)

A new similarity measure for covariate shift with applications to nonparametric regression. - Reese Pathak; Cong Ma 001; Martin J. Wainwright (ICML, 2022)

Optimally tackling covariate shift in RKHS-based nonparametric regression. - Cong Ma 001; Reese Pathak; Martin J. Wainwright (CoRR, 2022)

Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent. - Harry Dong; Tian Tong; Cong Ma 001; Yuejie Chi (CoRR, 2022)

$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games. - Yuepeng Yang; Cong Ma 001 (CoRR, 2022)

Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements. - Tian Tong; Cong Ma 001; Ashley Prater-Bennette; Erin E. Tripp; Yuejie Chi (J. Mach. Learn. Res., 2022)

Minimax Off-Policy Evaluation for Multi-Armed Bandits. - Cong Ma 001; Banghua Zhu; Jiantao Jiao; Martin J. Wainwright (IEEE Trans. Inf. Theory, 2022)

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. - Paria Rashidinejad; Banghua Zhu; Cong Ma 001; Jiantao Jiao; Stuart Russell 001 (IEEE Trans. Inf. Theory, 2022)

O(T-1 Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games. - Yuepeng Yang; Cong Ma 001 (ICLR, 2023)

The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing. - Xingyu Xu 001; Yandi Shen; Yuejie Chi; Cong Ma 001 (ICML, 2023)

Jump-Start Reinforcement Learning. - Ikechukwu Uchendu; Ted Xiao; Yao Lu 006; Banghua Zhu; Mengyuan Yan; Joséphine Simon; Matthew Bennice; Chuyuan Fu; Cong Ma 001; Jiantao Jiao; Sergey Levine; Karol Hausman (ICML, 2023)

Conformalized matrix completion. - Yu Gui; Rina Barber; Cong Ma 001 (NeurIPS, 2023)

Sharp high-probability sample complexities for policy evaluation with linear function approximation. - Gen Li 005; Weichen Wu; Yuejie Chi; Cong Ma 001; Alessandro Rinaldo; Yuting Wei 001 (CoRR, 2023)

Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage. - Yu Gui; Cong Ma 001; Yiqiao Zhong (CoRR, 2023)

Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization. - Cong Ma 001; Xingyu Xu 001; Tian Tong; Yuejie Chi (CoRR, 2023)

Optimal Tuning-Free Convex Relaxation for Noisy Matrix Completion. - Yuepeng Yang; Cong Ma 001 (IEEE Trans. Inf. Theory, 2023)

Top-K ranking with a monotone adversary. - Yuepeng Yang; Antares Chen; Lorenzo Orecchia; Cong Ma 001 (COLT, 2024)

Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift. - Jiawei Ge 003; Shange Tang; Jianqing Fan; Cong Ma 001; Chi Jin 001 (ICLR, 2024)

Off-policy estimation with adaptively collected data: the power of online learning. - Jeonghwan Lee; Cong Ma 001 (NeurIPS, 2024)

Random pairing MLE for estimation of item parameters in Rasch model. - Yuepeng Yang; Cong Ma 001 (CoRR, 2024)

Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimation. - Boxin Zhao; Cong Ma 001; Mladen Kolar (CoRR, 2024)

High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation. - Gen Li 005; Weichen Wu; Yuejie Chi; Cong Ma 001; Alessandro Rinaldo; Yuting Wei 001 (IEEE Trans. Inf. Theory, 2024)

Batched Nonparametric Contextual Bandits. - Rong Jiang; Cong Ma 001 (IEEE Trans. Inf. Theory, 2025)