An upper bound on multi-hop transmission capacity with dynamic routing selection. - Yuxin Chen 002; Jeffrey G. Andrews (ISIT, 2010)

An Upper Bound on Multi-hop Transmission Capacity with Dynamic Multipath Routing - Yuxin Chen 002; Jeffrey G. Andrews (CoRR, 2010)

Shannon meets Nyquist: The interplay between capacity and sampling. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (Allerton, 2011)

Shannon meets Nyquist: Capacity limits of sampled analog channels. - Yuxin Chen 002; Yonina C. Eldar; Andrea J. Goldsmith (ICASSP, 2011)

Sharing multiple messages over mobile networks. - Yuxin Chen 002; Sanjay Shakkottai; Jeffrey G. Andrews (INFOCOM, 2011)

Approaching the capacity of sampled analog channels. - Yuxin Chen 002; Yonina C. Eldar; Andrea J. Goldsmith (ITW, 2011)

Channel capacity under general nonuniform sampling. - Yuxin Chen 002; Yonina C. Eldar; Andrea J. Goldsmith (ISIT, 2012)

On the Role of Mobility for Multi-message Gossip - Yuxin Chen 002; Sanjay Shakkottai; Jeffrey G. Andrews (CoRR, 2012)

An Upper Bound on Multihop Transmission Capacity With Dynamic Routing Selection. - Yuxin Chen 002; Jeffrey G. Andrews (IEEE Trans. Inf. Theory, 2012)

Compressive recovery of 2-D off-grid frequencies. - Yuejie Chi; Yuxin Chen 002 (ACSSC, 2013)

Spectral Compressed Sensing via Structured Matrix Completion. - Yuxin Chen 002; Yuejie Chi (ICML (3), 2013)

Minimax universal sampling for compound multiband channels. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (ISIT, 2013)

Backing off from Infinity: Tight Performance Bounds for Large Random Vector Channels. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (CoRR, 2013)

Shannon Meets Nyquist: Capacity of Sampled Gaussian Channels. - Yuxin Chen 002; Yonina C. Eldar; Andrea J. Goldsmith (IEEE Trans. Inf. Theory, 2013)

On the Role of Mobility for Multimessage Gossip. - Yuxin Chen 002; Sanjay Shakkottai; Jeffrey G. Andrews (IEEE Trans. Inf. Theory, 2013)

Estimation of simultaneously structured covariance matrices from quadratic measurements. - Yuxin Chen 002; Yuejie Chi; Andrea J. Goldsmith (ICASSP, 2014)

An algorithm for exact super-resolution and phase retrieval. - Yuxin Chen 002; Yonina C. Eldar; Andrea J. Goldsmith (ICASSP, 2014)

Near-Optimal Joint Object Matching via Convex Relaxation. - Yuxin Chen 002; Leonidas J. Guibas; Qi-Xing Huang (ICML, 2014)

Scalable Semidefinite Relaxation for Maximum A Posterior Estimation. - Qi-Xing Huang; Yuxin Chen 002; Leonidas J. Guibas (ICML, 2014)

Robust and universal covariance estimation from quadratic measurements via convex programming. - Yuxin Chen 002; Yuejie Chi; Andrea J. Goldsmith (ISIT, 2014)

Information recovery from pairwise measurements. - Yuxin Chen 002; Andrea J. Goldsmith (ISIT, 2014)

Robust Spectral Compressed Sensing via Structured Matrix Completion. - Yuxin Chen 002; Yuejie Chi (IEEE Trans. Inf. Theory, 2014)

Channel Capacity Under Sub-Nyquist Nonuniform Sampling. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (IEEE Trans. Inf. Theory, 2014)

Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons. - Yuxin Chen 002; Changho Suh (ICML, 2015)

Information recovery from pairwise measurements: A shannon-theoretic approach. - Yuxin Chen 002; Changho Suh; Andrea J. Goldsmith (ISIT, 2015)

Top-K ranking: An information-theoretic perspective. - Yuxin Chen 002; Changho Suh (ITW Fall, 2015)

Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems. - Yuxin Chen 002; Emmanuel J. Candès (NIPS, 2015)

Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming. - Yuxin Chen 002; Yuejie Chi; Andrea J. Goldsmith (IEEE Trans. Inf. Theory, 2015)

Backing Off From Infinity: Performance Bounds via Concentration of Spectral Measure for Random MIMO Channels. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (IEEE Trans. Inf. Theory, 2015)

Compressive Two-Dimensional Harmonic Retrieval via Atomic Norm Minimization. - Yuejie Chi; Yuxin Chen 002 (IEEE Trans. Signal Process., 2015)

Community Recovery in Graphs with Locality. - Yuxin Chen 002; Govinda M. Kamath; Changho Suh; David Tse (ICML, 2016)

The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences. - Yuxin Chen 002; Emmanuel J. Candès (CoRR, 2016)

Information Recovery From Pairwise Measurements. - Yuxin Chen 002; Changho Suh; Andrea J. Goldsmith (IEEE Trans. Inf. Theory, 2016)

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

The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square. - Pragya Sur; Yuxin Chen 002; Emmanuel J. Candès (CoRR, 2017)

On the Minimax Capacity Loss Under Sub-Nyquist Universal Sampling. - Yuxin Chen 002; Andrea J. Goldsmith; Yonina C. Eldar (IEEE Trans. Inf. Theory, 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)

Asymmetry Helps: Eigenvalue and Eigenvector Analyses of Asymmetrically Perturbed Low-Rank Matrices. - Yuxin Chen 002; Chen Cheng; Jianqing Fan (CoRR, 2018)

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

Communication-Efficient Distributed Optimization in Networks with Gradient Tracking. - Boyue Li; Shicong Cen; Yuxin Chen 002; Yuejie Chi (CoRR, 2019)

Subspace Estimation from Unbalanced and Incomplete Data Matrices: 𝓁2, ∞ Statistical Guarantees. - Changxiao Cai; Gen Li 005; Yuejie Chi; H. Vincent Poor; Yuxin Chen 002 (CoRR, 2019)

Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data. - Changxiao Cai; Gen Li 005; H. Vincent Poor; Yuxin Chen 002 (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)

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. - Yuejie Chi; Yue M. Lu; Yuxin Chen 002 (IEEE Trans. Signal Process., 2019)

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuantao Gu; Yuxin Chen 002 (NeurIPS, 2020)

Inference for linear forms of eigenvectors under minimal eigenvalue separation: Asymmetry and heteroscedasticity. - Chen Cheng; Yuting Wei 001; Yuxin Chen 002 (CoRR, 2020)

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)

Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution. - Yuxin Chen 002; Jianqing Fan; Bingyan Wang; 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)

Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction. - Boyue Li; Shicong Cen; Yuxin Chen 002; Yuejie Chi (J. Mach. Learn. Res., 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)

Softmax Policy Gradient Methods Can Take Exponential Time to Converge. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuantao Gu; Yuxin Chen 002 (COLT, 2021)

Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. - Gen Li 005; Changxiao Cai; Yuxin Chen 002; Yuantao Gu; Yuting Wei 001; Yuejie Chi (ICML, 2021)

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. - Gen Li 005; Yuxin Chen 002; Yuejie Chi; Yuantao Gu; Yuting Wei 001 (NeurIPS, 2021)

Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. - Gen Li 005; Laixi Shi; Yuxin Chen 002; Yuantao Gu; Yuejie Chi (NeurIPS, 2021)

Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen-Gaps. - Gen Li 005; Changxiao Cai; Yuantao Gu; H. Vincent Poor; Yuxin Chen 002 (CoRR, 2021)

Inference for Heteroskedastic PCA with Missing Data. - Yuling Yan; Yuxin Chen 002; Jianqing Fan (CoRR, 2021)

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

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

Tackling Small Eigen-Gaps: Fine-Grained Eigenvector Estimation and Inference Under Heteroscedastic Noise. - Chen Cheng; Yuting Wei 001; 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)

MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation. - Xiangjin Xie; Yuxin Chen 002; Ruipeng Wang; Xianli Zhang; Shilei Cao 001; Kai Ouyang; Zihan Zhang; Hai-Tao Zheng 002; Buyue Qian; Hansen Zheng; Bo Hu; Chengxiang Zhuo; et al. (ICDM, 2022)

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. - Laixi Shi; Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (ICML, 2022)

Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model. - Gen Li 005; Yuejie Chi; Yuting Wei 001; Yuxin Chen 002 (NeurIPS, 2022)

Settling the Sample Complexity of Model-Based Offline Reinforcement Learning. - Gen Li 005; Laixi Shi; Yuxin Chen 002; Yuejie Chi; Yuting Wei 001 (CoRR, 2022)

Model-Based Reinforcement Learning Is Minimax-Optimal for Offline Zero-Sum Markov Games. - Yuling Yan; Gen Li 005; Yuxin Chen 002; Jianqing Fan (CoRR, 2022)

Minimax-Optimal Multi-Agent RL in Zero-Sum Markov Games With a Generative Model. - Gen Li 005; Yuejie Chi; Yuting Wei 001; Yuxin Chen 002 (CoRR, 2022)

Nonconvex Low-Rank Tensor Completion from Noisy Data. - Changxiao Cai; Gen Li 005; H. Vincent Poor; Yuxin Chen 002 (Oper. Res., 2022)

Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization. - Shicong Cen; Chen Cheng; Yuxin Chen 002; Yuting Wei 001; Yuejie Chi (Oper. Res., 2022)

Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuantao Gu; Yuxin Chen 002 (IEEE Trans. Inf. Theory, 2022)

Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning. - Gen Li 005; Wenhao Zhan; Jason D. Lee; Yuejie Chi; Yuxin Chen 002 (NeurIPS, 2023)

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. - Laixi Shi; Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Matthieu Geist; Yuejie Chi (NeurIPS, 2023)

Embedding Transfer with Enhanced Correlation Modeling for Cross-Domain Recommendation. - Shilei Cao 001; Yujie Lin; Xianli Zhang; Yufu Chen; Zhen Zhu; Yuxin Chen 002; Buyue Qian; Feng Wang; Zang Li (SDM, 2023)

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods. - Gen Li 005; Yanxi Chen 001; Yuejie Chi; H. Vincent Poor; Yuxin Chen 002 (CoRR, 2023)

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models. - Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (CoRR, 2023)

Federated Natural Policy Gradient Methods for Multi-task Reinforcement Learning. - Tong Yang 007; Shicong Cen; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (CoRR, 2023)

Softmax policy gradient methods can take exponential time to converge. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuxin Chen 002 (Math. Program., 2023)

Uncertainty Quantification for Nonconvex Tensor Completion: Confidence Intervals, Heteroscedasticity and Optimality. - Changxiao Cai; H. Vincent Poor; Yuxin Chen 002 (IEEE Trans. Inf. Theory, 2023)

Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. - Wenhao Zhan; Shicong Cen; Baihe Huang; Yuxin Chen 002; Jason D. Lee; Yuejie Chi (SIAM J. Optim., 2023)

The Efficacy of Pessimism in Asynchronous Q-Learning. - Yuling Yan; Gen Li 005; Yuxin Chen 002; Jianqing Fan (IEEE Trans. Inf. Theory, 2023)

Minimax-optimal reward-agnostic exploration in reinforcement learning. - Gen Li 005; Yuling Yan; Yuxin Chen 002; Jianqing Fan (COLT, 2024)

Optimal Multi-Distribution Learning. - Zihan Zhang; Wenhao Zhan; Yuxin Chen 002; Simon S. Du; Jason D. Lee (COLT, 2024)

Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models. - Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (ICLR, 2024)

Horizon-Free Regret for Linear Markov Decision Processes. - Zihan Zhang; Jason D. Lee; Yuxin Chen 002; Simon Shaolei Du (ICLR, 2024)

Accelerating Convergence of Score-Based Diffusion Models, Provably. - Gen Li 005; Yu Huang 023; Timofey Efimov; Yuting Wei 001; Yuejie Chi; Yuxin Chen 002 (ICML, 2024)

Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning. - Tong Yang 007; Shicong Cen; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (NeurIPS, 2024)

A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuxin Chen 002 (CoRR, 2024)

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis. - Gen Li 005; Changxiao Cai; Yuxin Chen 002; Yuting Wei 001; Yuejie Chi (Oper. Res., 2024)

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. - Gen Li 005; Yuting Wei 001; Yuejie Chi; Yuxin Chen 002 (Oper. Res., 2024)

Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games. - Yuling Yan; Gen Li 005; Yuxin Chen 002; Jianqing Fan (Oper. Res., 2024)

Anytime Acceleration of Gradient Descent. - Zihan Zhang; Jason D. Lee; Simon S. Du; Yuxin Chen 002 (COLT, 2025)

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods. - Gen Li 005; Yanxi Chen 001; Yu Huang 023; Yuejie Chi; H. Vincent Poor; Yuxin Chen 002 (SIAM J. Optim., 2025)

MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation. - Xiangjin Xie; Yuxin Chen 002; Ruipeng Wang; Kai Ouyang; Zihan Zhang; Hai-Tao Zheng 002; Buyue Qian; Hansen Zheng; Bo Hu; Chengxiang Zhuo; Zang Li (CoRR, 2025)

Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen-Gaps. - Gen Li 005; Changxiao Cai; H. Vincent Poor; Yuxin Chen 002 (IEEE Trans. Inf. Theory, 2025)

Settling the Sample Complexity of Online Reinforcement Learning. - Zihan Zhang; Yuxin Chen 002; Jason D. Lee; Simon S. Du (J. ACM, 2025)

Statistical and Algorithmic Foundations of Reinforcement Learning. - Yuejie Chi; Yuxin Chen 002; Yuting Wei 001 (CoRR, 2025)