Jiaming Xu

Orcid: 0000-0001-6104-4742

Affiliations:
  • Duke University, Fuqua School of Business, Durham, NC, USA
  • Purdue University, Krannert School of Management, West Lafayette, IN, USA (2016 - 2018)
  • University of Pennsylvania, Wharton School, Department of Statistics, Philadelphia, PA, USA (2015)
  • University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, IL, USA (PhD 2014)
  • University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, TX, USA (until 2011)


According to our database1, Jiaming Xu authored at least 78 papers between 2010 and 2025.

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Bibliography

2025
The Planted Spanning Tree Problem.
CoRR, February, 2025

The Planted Spanning Tree Problems: Exact Overlap Characterization via Local Weak Convergence Extended Abstract.
Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024
Global Convergence of Federated Learning for Mixed Regression.
IEEE Trans. Inf. Theory, September, 2024

Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent.
J. Mach. Learn. Res., 2024

Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms.
CoRR, 2024

Sharp Information-Theoretic Thresholds for Shuffled Linear Regression.
Proceedings of the IEEE International Symposium on Information Theory, 2024

2023
Spectral Graph Matching and Regularized Quadratic Relaxations II.
Found. Comput. Math., October, 2023

Spectral Graph Matching and Regularized Quadratic Relaxations I Algorithm and Gaussian Analysis.
Found. Comput. Math., October, 2023

Learner-Private Convex Optimization.
IEEE Trans. Inf. Theory, 2023

A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points.
J. Mach. Learn. Res., 2023

Federated Learning in the Presence of Adversarial Client Unavailability.
CoRR, 2023

Random Graph Matching at Otter's Threshold via Counting Chandeliers.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Constant Regret Primal-Dual Policy for Multi-way Dynamic Matching.
Proceedings of the Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2023

SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching.
Proceedings of the International Conference on Machine Learning, 2023

2022
Settling the Sharp Reconstruction Thresholds of Random Graph Matching.
IEEE Trans. Inf. Theory, 2022

Integrated Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs.
Oper. Res., 2022

SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching.
CoRR, 2022

Random Graph Matching in Geometric Models: the Case of Complete Graphs.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Consistent Recovery Threshold of Hidden Nearest Neighbor Graphs.
IEEE Trans. Inf. Theory, 2021

The Power of D-hops in Matching Power-Law Graphs.
Proc. ACM Meas. Anal. Comput. Syst., 2021

Graph Matching with Partially-Correct Seeds.
J. Mach. Learn. Res., 2021

Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points.
CoRR, 2021

The planted matching problem: Sharp threshold and infinite-order phase transition.
CoRR, 2021

Learner-Private Online Convex Optimization.
CoRR, 2021

One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Optimal query complexity for private sequential learning against eavesdropping.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Seeded graph matching via large neighborhood statistics.
Random Struct. Algorithms, 2020

Hidden Hamiltonian Cycle Recovery via Linear Programming.
Oper. Res., 2020

Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Securing Distributed Gradient Descent in High Dimensional Statistical Learning.
Proc. ACM Meas. Anal. Comput. Syst., 2019

The Planted Matching Problem: Phase Transitions and Exact Results.
CoRR, 2019

Optimal query complexity for private sequential learning.
CoRR, 2019

Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality.
CoRR, 2019

Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model.
CoRR, 2019

Improved Queue-Size Scaling for Input-Queued Switches via Graph Factorization.
Proceedings of the Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems, 2019

The All-or-Nothing Phenomenon in Sparse Linear Regression.
Proceedings of the Conference on Learning Theory, 2019

All-or-Nothing Phenomena: From Single-Letter to High Dimensions.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization.
IEEE Trans. Inf. Theory, 2018

Learning from Comparisons and Choices.
J. Mach. Learn. Res., 2018

Recovering a hidden community beyond the Kesten-Stigum threshold in O(|E|log*|V|) time.
J. Appl. Probab., 2018

Efficient random graph matching via degree profiles.
CoRR, 2018

Convex Relaxation Methods for Community Detection.
CoRR, 2018

Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits.
CoRR, 2018

Securing Distributed Machine Learning in High Dimensions.
CoRR, 2018

Integrating Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs.
Proceedings of the 2018 Information Theory and Applications Workshop, 2018

Rates of Convergence of Spectral Methods for Graphon Estimation.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Information Limits for Recovering a Hidden Community.
IEEE Trans. Inf. Theory, 2017

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent.
Proc. ACM Meas. Anal. Comput. Syst., 2017

Submatrix localization via message passing.
J. Mach. Learn. Res., 2017

2016
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions.
IEEE Trans. Inf. Theory, 2016

Achieving Exact Cluster Recovery Threshold via Semidefinite Programming.
IEEE Trans. Inf. Theory, 2016

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices.
J. Mach. Learn. Res., 2016

Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization.
CoRR, 2016

Mutual information in rank-one matrix estimation.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

Local Algorithms for Block Models with Side Information.
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

Density Evolution in the Degree-correlated Stochastic Block Model.
Proceedings of the 29th Conference on Learning Theory, 2016

Semidefinite Programs for Exact Recovery of a Hidden Community.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Reconstruction in the Labelled Stochastic Block Model.
IEEE Trans. Netw. Sci. Eng., 2015

Recovering a Hidden Community Beyond the Spectral Limit in O(|E|log<sup>*</sup>|V|) Time.
CoRR, 2015

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models.
CoRR, 2015

Clustering and Inference From Pairwise Comparisons.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Collaboratively Learning Preferences from Ordinal Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Exact recovery threshold in the binary censored block model.
Proceedings of the 2015 IEEE Information Theory Workshop, 2015

Computational Lower Bounds for Community Detection on Random Graphs.
Proceedings of The 28th Conference on Learning Theory, 2015

Achieving exact cluster recovery threshold via semidefinite programming under the stochastic block model.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014
Statistical inference in networks: fundamental limits and efficient algorithms
PhD thesis, 2014

Jointly clustering rows and columns of binary matrices: algorithms and trade-offs.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

Minimax-optimal Inference from Partial Rankings.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting.
Proceedings of the 31th International Conference on Machine Learning, 2014

Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Reconstruction in the labeled stochastic block model.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013

2012
MISO Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe?
IEEE Trans. Wirel. Commun., 2012

The supermarket game.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
On the Accuracy of the Wyner Model in Cellular Networks.
IEEE Trans. Wirel. Commun., 2011

Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe?
CoRR, 2011

On the Accuracy of the Wyner Model in Downlink Cellular Networks.
Proceedings of IEEE International Conference on Communications, 2011

The net benefit of delayed finite-rate feedback in the MISO broadcast channel.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
When Does the Wyner Model Accurately Describe an Uplink Cellular Network?
Proceedings of the Global Communications Conference, 2010


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