When Does the Wyner Model Accurately Describe an Uplink Cellular Network? - Jiaming Xu 002; Jun Zhang 004; Jeffrey G. Andrews (GLOBECOM, 2010)

The net benefit of delayed finite-rate feedback in the MISO broadcast channel. - Jiaming Xu 002; Jeffrey G. Andrews; Syed Ali Jafar (Allerton, 2011)

On the Accuracy of the Wyner Model in Downlink Cellular Networks. - Jiaming Xu 002; Jun Zhang 004; Jeffrey G. Andrews (ICC, 2011)

Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe? - Jiaming Xu 002; Jeffrey G. Andrews; Syed Ali Jafar (CoRR, 2011)

On the Accuracy of the Wyner Model in Cellular Networks. - Jiaming Xu 002; Jun Zhang 004; Jeffrey G. Andrews (IEEE Trans. Wirel. Commun., 2011)

The supermarket game. - Jiaming Xu 002; Bruce E. Hajek (ISIT, 2012)

MISO Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe? - Jiaming Xu 002; Jeffrey G. Andrews; Syed Ali Jafar (IEEE Trans. Wirel. Commun., 2012)

Reconstruction in the labeled stochastic block model. - Marc Lelarge; Laurent Massoulié; Jiaming Xu 002 (ITW, 2013)

Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results. - Jiaming Xu 002; Laurent Massoulié; Marc Lelarge (COLT, 2014)

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting. - Yudong Chen 001; Jiaming Xu 002 (ICML, 2014)

Minimax-optimal Inference from Partial Rankings. - Bruce E. Hajek; Sewoong Oh; Jiaming Xu 002 (NIPS, 2014)

Jointly clustering rows and columns of binary matrices: algorithms and trade-offs. - Jiaming Xu 002; Rui Wu 009; Kai Zhu 002; Bruce E. Hajek; R. Srikant 001; Lei Ying 001 (SIGMETRICS, 2014)

Statistical inference in networks: fundamental limits and efficient algorithms - Jiaming Xu 002 (2014)

Achieving exact cluster recovery threshold via semidefinite programming under the stochastic block model. - Yihong Wu 001; Jiaming Xu 002; Bruce E. Hajek (ACSSC, 2015)

Computational Lower Bounds for Community Detection on Random Graphs. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (COLT, 2015)

Exact recovery threshold in the binary censored block model. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (ITW Fall, 2015)

Collaboratively Learning Preferences from Ordinal Data. - Sewoong Oh; Kiran Koshy Thekumparampil; Jiaming Xu 002 (NIPS, 2015)

Clustering and Inference From Pairwise Comparisons. - Rui Wu 009; Jiaming Xu 002; Rayadurgam Srikant; Laurent Massoulié; Marc Lelarge; Bruce E. Hajek (SIGMETRICS, 2015)

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models. - Yudong Chen 001; Xiaodong Li; Jiaming Xu 002 (CoRR, 2015)

Recovering a Hidden Community Beyond the Spectral Limit in O(|E|log*|V|) Time. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (CoRR, 2015)

Reconstruction in the Labelled Stochastic Block Model. - Marc Lelarge; Laurent Massoulié; Jiaming Xu 002 (IEEE Trans. Netw. Sci. Eng., 2015)

Semidefinite Programs for Exact Recovery of a Hidden Community. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (COLT, 2016)

Density Evolution in the Degree-correlated Stochastic Block Model. - Elchanan Mossel; Jiaming Xu 002 (COLT, 2016)

Local Algorithms for Block Models with Side Information. - Elchanan Mossel; Jiaming Xu 002 (ITCS, 2016)

Mutual information in rank-one matrix estimation. - Florent Krzakala; Jiaming Xu 002; Lenka Zdeborová (ITW, 2016)

Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization. - Jess Banks; Cristopher Moore; Roman Vershynin; Jiaming Xu 002 (CoRR, 2016)

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices. - Yudong Chen 001; Jiaming Xu 002 (J. Mach. Learn. Res., 2016)

Achieving Exact Cluster Recovery Threshold via Semidefinite Programming. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (IEEE Trans. Inf. Theory, 2016)

Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (IEEE Trans. Inf. Theory, 2016)

Submatrix localization via message passing. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (J. Mach. Learn. Res., 2017)

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. - Yudong Chen 001; Lili Su; Jiaming Xu 002 (Proc. ACM Meas. Anal. Comput. Syst., 2017)

Information Limits for Recovering a Hidden Community. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (IEEE Trans. Inf. Theory, 2017)

Rates of Convergence of Spectral Methods for Graphon Estimation. - Jiaming Xu 002 (ICML, 2018)

Integrating Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs. - Wei-Kang Hsu; Jiaming Xu 002; Xiaojun Lin 001; Mark R. Bell (ITA, 2018)

Securing Distributed Machine Learning in High Dimensions. - Lili Su; Jiaming Xu 002 (CoRR, 2018)

Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits. - Yihong Wu 001; Jiaming Xu 002 (CoRR, 2018)

Convex Relaxation Methods for Community Detection. - Xiaodong Li; Yudong Chen 001; Jiaming Xu 002 (CoRR, 2018)

Efficient random graph matching via degree profiles. - Jian Ding; Zongming Ma; Yihong Wu 001; Jiaming Xu 002 (CoRR, 2018)

Recovering a hidden community beyond the Kesten-Stigum threshold in O(|E|log*|V|) time. - Bruce E. Hajek; Yihong Wu 001; Jiaming Xu 002 (J. Appl. Probab., 2018)

Learning from Comparisons and Choices. - Sahand Negahban; Sewoong Oh; Kiran Koshy Thekumparampil; Jiaming Xu 002 (J. Mach. Learn. Res., 2018)

Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization. - Jess Banks; Cristopher Moore; Roman Vershynin; Nicolas Verzelen; Jiaming Xu 002 (IEEE Trans. Inf. Theory, 2018)

All-or-Nothing Phenomena: From Single-Letter to High Dimensions. - Galen Reeves; Jiaming Xu 002; Ilias Zadik (CAMSAP, 2019)

The All-or-Nothing Phenomenon in Sparse Linear Regression. - Galen Reeves; Jiaming Xu 002; Ilias Zadik (COLT, 2019)

Improved Queue-Size Scaling for Input-Queued Switches via Graph Factorization. - Jiaming Xu 002; Yuan Zhong (SIGMETRICS (Abstracts), 2019)

Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model. - Zhou Fan; Cheng Mao; Yihong Wu 001; Jiaming Xu 002 (CoRR, 2019)

Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality. - Zhou Fan; Cheng Mao; Yihong Wu 001; Jiaming Xu 002 (CoRR, 2019)

Optimal query complexity for private sequential learning. - Jiaming Xu 002; Dana Yang (CoRR, 2019)

The Planted Matching Problem: Phase Transitions and Exact Results. - Mehrdad Moharrami; Cristopher Moore; Jiaming Xu 002 (CoRR, 2019)

Securing Distributed Gradient Descent in High Dimensional Statistical Learning. - Lili Su; Jiaming Xu 002 (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory. - Zhou Fan; Cheng Mao; Yihong Wu 001; Jiaming Xu 002 (ICML, 2020)

Hidden Hamiltonian Cycle Recovery via Linear Programming. - Vivek Kumar Bagaria; Jian Ding; David Tse; Yihong Wu 001; Jiaming Xu 002 (Oper. Res., 2020)

Seeded graph matching via large neighborhood statistics. - Elchanan Mossel; Jiaming Xu 002 (Random Struct. Algorithms, 2020)

Optimal query complexity for private sequential learning against eavesdropping. - Jiaming Xu 002; Kuang Xu; Dana Yang (AISTATS, 2021)

One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks. - Hanjing Zhu; Jiaming Xu 002 (AISTATS, 2021)

Learner-Private Online Convex Optimization. - Jiaming Xu 002; Kuang Xu; Dana Yang (CoRR, 2021)

The planted matching problem: Sharp threshold and infinite-order phase transition. - Jian Ding; Yihong Wu 001; Jiaming Xu 002; Dana Yang (CoRR, 2021)

Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points. - Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2021)

Graph Matching with Partially-Correct Seeds. - Liren Yu; Jiaming Xu 002; Xiaojun Lin 001 (J. Mach. Learn. Res., 2021)

The Power of D-hops in Matching Power-Law Graphs. - Liren Yu; Jiaming Xu 002; Xiaojun Lin 001 (Proc. ACM Meas. Anal. Comput. Syst., 2021)

Consistent Recovery Threshold of Hidden Nearest Neighbor Graphs. - Jian Ding; Yihong Wu 001; Jiaming Xu 002; Dana Yang (IEEE Trans. Inf. Theory, 2021)

Random Graph Matching in Geometric Models: the Case of Complete Graphs. - Haoyu Wang; Yihong Wu 001; Jiaming Xu 002; Israel Yolou (COLT, 2022)

SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching. - Liren Yu; Jiaming Xu 002; Xiaojun Lin 001 (CoRR, 2022)

Integrated Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs. - Wei-Kang Hsu; Jiaming Xu 002; Xiaojun Lin 001; Mark R. Bell (Oper. Res., 2022)

Settling the Sharp Reconstruction Thresholds of Random Graph Matching. - Yihong Wu 001; Jiaming Xu 002; Sophie H. Yu (IEEE Trans. Inf. Theory, 2022)

SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching. - Liren Yu; Jiaming Xu 002; Xiaojun Lin 001 (ICML, 2023)

Constant Regret Primal-Dual Policy for Multi-way Dynamic Matching. - Yehua Wei; Jiaming Xu 002; Sophie H. Yu (SIGMETRICS (Abstracts), 2023)

Random Graph Matching at Otter's Threshold via Counting Chandeliers. - Cheng Mao; Yihong Wu 001; Jiaming Xu 002; Sophie H. Yu (STOC, 2023)

Federated Learning in the Presence of Adversarial Client Unavailability. - Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2023)

A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points. - Lili Su; Jiaming Xu 002; Pengkun Yang (J. Mach. Learn. Res., 2023)

Learner-Private Convex Optimization. - Jiaming Xu 002; Kuang Xu; Dana Yang (IEEE Trans. Inf. Theory, 2023)

Spectral Graph Matching and Regularized Quadratic Relaxations I Algorithm and Gaussian Analysis. - Zhou Fan; Cheng Mao; Yihong Wu 001; Jiaming Xu 002 (Found. Comput. Math., 2023)

Spectral Graph Matching and Regularized Quadratic Relaxations II. - Zhou Fan; Cheng Mao; Yihong Wu 001; Jiaming Xu 002 (Found. Comput. Math., 2023)

Sharp Information-Theoretic Thresholds for Shuffled Linear Regression. - Leon Lufkin; Yihong Wu 001; Jiaming Xu 002 (ISIT, 2024)

Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms. - Xiaochun Niu; Lili Su; Jiaming Xu 002; Pengkun Yang (CoRR, 2024)

Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent. - Jiaming Xu 002; Hanjing Zhu (J. Mach. Learn. Res., 2024)

Global Convergence of Federated Learning for Mixed Regression. - Lili Su; Jiaming Xu 002; Pengkun Yang (IEEE Trans. Inf. Theory, 2024)

The Planted Spanning Tree Problems: Exact Overlap Characterization via Local Weak Convergence Extended Abstract. - Mehrdad Moharrami; Cristopher Moore; Jiaming Xu 002 (COLT, 2025)

The Planted Spanning Tree Problem. - Mehrdad Moharrami; Cristopher Moore; Jiaming Xu 002 (CoRR, 2025)