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ORCIDJiaming Xu 0002
Person information
- affiliation: Duke University, Fuqua School of Business, Durham, NC, USA
- affiliation (2016 - 2018): Purdue University, Krannert School of Management, West Lafayette, IN, USA
- affiliation (2015): University of Pennsylvania, Wharton School, Department of Statistics, Philadelphia, PA, USA
- affiliation (PhD 2014): University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, IL, USA
- affiliation (until 2011): University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, TX, USA
Other persons with the same name
- Jiaming Xu — disambiguation page
- Jiaming Xu 0001
![[0000-0001-7635-1059]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-7635-1059")
— Chinese Academy of Sciences, Institute of Automation, Beijing, China
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Books and Theses
- 2014
[b1]Jiaming Xu:
Statistical inference in networks: fundamental limits and efficient algorithms. University of Illinois Urbana-Champaign, USA, 2014
Journal Articles
- 2024
- [j26]Jiaming Xu, Hanjing Zhu:
Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent. J. Mach. Learn. Res. 25: 94:1-94:83 (2024) - [j25]Lili Su, Jiaming Xu, Pengkun Yang:
Global Convergence of Federated Learning for Mixed Regression. IEEE Trans. Inf. Theory 70(9): 6391-6411 (2024) - 2023
- [j24]Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu:
Spectral Graph Matching and Regularized Quadratic Relaxations I Algorithm and Gaussian Analysis. Found. Comput. Math. 23(5): 1511-1565 (2023) - [j23]Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu:
Spectral Graph Matching and Regularized Quadratic Relaxations II. Found. Comput. Math. 23(5): 1567-1617 (2023) - [j22]Lili Su, Jiaming Xu, Pengkun Yang:
A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points. J. Mach. Learn. Res. 24: 203:1-203:48 (2023) - [j21]Jiaming Xu, Kuang Xu, Dana Yang:
Learner-Private Convex Optimization. IEEE Trans. Inf. Theory 69(1): 528-547 (2023) - 2022
- [j20]Wei-Kang Hsu, Jiaming Xu, Xiaojun Lin, Mark R. Bell:
Integrated Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs. Oper. Res. 70(2): 1166-1181 (2022) - [j19]Yihong Wu, Jiaming Xu, Sophie H. Yu:
Settling the Sharp Reconstruction Thresholds of Random Graph Matching. IEEE Trans. Inf. Theory 68(8): 5391-5417 (2022) - 2021
- [j18]Liren Yu, Jiaming Xu, Xiaojun Lin:
Graph Matching with Partially-Correct Seeds. J. Mach. Learn. Res. 22: 280:1-280:54 (2021) - [j17]Liren Yu, Jiaming Xu, Xiaojun Lin:
The Power of D-hops in Matching Power-Law Graphs. Proc. ACM Meas. Anal. Comput. Syst. 5(2): 27:1-27:43 (2021) - [j16]Jian Ding, Yihong Wu, Jiaming Xu, Dana Yang:
Consistent Recovery Threshold of Hidden Nearest Neighbor Graphs. IEEE Trans. Inf. Theory 67(8): 5211-5229 (2021) - 2020
- [j15]Vivek Kumar Bagaria, Jian Ding, David Tse, Yihong Wu, Jiaming Xu:
Hidden Hamiltonian Cycle Recovery via Linear Programming. Oper. Res. 68(1): 53-70 (2020) - [j14]Elchanan Mossel, Jiaming Xu:
Seeded graph matching via large neighborhood statistics. Random Struct. Algorithms 57(3): 570-611 (2020) - 2019
- [j13]Lili Su, Jiaming Xu:
Securing Distributed Gradient Descent in High Dimensional Statistical Learning. Proc. ACM Meas. Anal. Comput. Syst. 3(1): 12:1-12:41 (2019) - 2018
- [j12]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Recovering a hidden community beyond the Kesten-Stigum threshold in O(|E|log*|V|) time. J. Appl. Probab. 55(2): 325-352 (2018) - [j11]Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Learning from Comparisons and Choices. J. Mach. Learn. Res. 19: 40:1-40:95 (2018) - [j10]Jess Banks, Cristopher Moore, Roman Vershynin, Nicolas Verzelen, Jiaming Xu:
Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization. IEEE Trans. Inf. Theory 64(7): 4872-4894 (2018) - 2017
- [j9]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Submatrix localization via message passing. J. Mach. Learn. Res. 18: 186:1-186:52 (2017) - [j8]Yudong Chen, Lili Su, Jiaming Xu:
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. Proc. ACM Meas. Anal. Comput. Syst. 1(2): 44:1-44:25 (2017) - [j7]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Information Limits for Recovering a Hidden Community. IEEE Trans. Inf. Theory 63(8): 4729-4745 (2017) - 2016
- [j6]Yudong Chen, Jiaming Xu:
Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices. J. Mach. Learn. Res. 17: 27:1-27:57 (2016) - [j5]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming. IEEE Trans. Inf. Theory 62(5): 2788-2797 (2016) - [j4]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions. IEEE Trans. Inf. Theory 62(10): 5918-5937 (2016) - 2015
- [j3]Marc Lelarge, Laurent Massoulié, Jiaming Xu:
Reconstruction in the Labelled Stochastic Block Model. IEEE Trans. Netw. Sci. Eng. 2(4): 152-163 (2015) - 2012
- [j2]Jiaming Xu, Jeffrey G. Andrews, Syed Ali Jafar:
MISO Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe? IEEE Trans. Wirel. Commun. 11(4): 1456-1467 (2012) - 2011
- [j1]Jiaming Xu, Jun Zhang, Jeffrey G. Andrews:
On the Accuracy of the Wyner Model in Cellular Networks. IEEE Trans. Wirel. Commun. 10(9): 3098-3109 (2011)
Conference and Workshop Papers
- 2024
- [c42]Leon Lufkin, Yihong Wu, Jiaming Xu:
Sharp Information-Theoretic Thresholds for Shuffled Linear Regression. ISIT 2024: 363-367 - 2023
- [c41]Liren Yu, Jiaming Xu, Xiaojun Lin:
SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching. ICML 2023: 40390-40411 - [c40]Yehua Wei, Jiaming Xu, Sophie H. Yu:
Constant Regret Primal-Dual Policy for Multi-way Dynamic Matching. SIGMETRICS (Abstracts) 2023: 79-80 - [c39]Cheng Mao, Yihong Wu, Jiaming Xu, Sophie H. Yu:
Random Graph Matching at Otter's Threshold via Counting Chandeliers. STOC 2023: 1345-1356 - 2022
- [c38]Haoyu Wang, Yihong Wu, Jiaming Xu, Israel Yolou:
Random Graph Matching in Geometric Models: the Case of Complete Graphs. COLT 2022: 3441-3488 - [c37]Lili Su, Jiaming Xu, Pengkun Yang:
Global Convergence of Federated Learning for Mixed Regression. NeurIPS 2022 - 2021
- [c36]Jiaming Xu, Kuang Xu, Dana Yang:
Optimal query complexity for private sequential learning against eavesdropping. AISTATS 2021: 2296-2304 - [c35]Hanjing Zhu, Jiaming Xu:
One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks. AISTATS 2021: 3673-3681 - [c34]Jiaming Xu, Kuang Xu, Dana Yang:
Learner-Private Convex Optimization. ICML 2021: 11570-11580 - [c33]Yihong Wu, Jiaming Xu, Sophie H. Yu:
Settling the Sharp Reconstruction Thresholds of Random Graph Matching. ISIT 2021: 2714-2719 - [c32]Liren Yu, Jiaming Xu, Xiaojun Lin:
The Power of D-hops in Matching Power-Law Graphs. SIGMETRICS (Abstracts) 2021: 77-78 - 2020
- [c31]Jian Ding, Yihong Wu, Jiaming Xu, Dana Yang:
Consistent recovery threshold of hidden nearest neighbor graphs. COLT 2020: 1540-1553 - [c30]Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu:
Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory. ICML 2020: 2985-2995 - 2019
- [c29]Galen Reeves, Jiaming Xu, Ilias Zadik:
All-or-Nothing Phenomena: From Single-Letter to High Dimensions. CAMSAP 2019: 654-658 - [c28]Galen Reeves, Jiaming Xu, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Linear Regression. COLT 2019: 2652-2663 - [c27]Jiaming Xu, Yuan Zhong:
Improved Queue-Size Scaling for Input-Queued Switches via Graph Factorization. SIGMETRICS (Abstracts) 2019: 67-68 - [c26]Lili Su, Jiaming Xu:
Securing Distributed Gradient Descent in High Dimensional Statistical Learning. SIGMETRICS (Abstracts) 2019: 83-84 - [c25]Elchanan Mossel, Jiaming Xu:
Seeded Graph Matching via Large Neighborhood Statistics. SODA 2019: 1005-1014 - 2018
- [c24]Jiaming Xu:
Rates of Convergence of Spectral Methods for Graphon Estimation. ICML 2018: 5429-5438 - [c23]Wei-Kang Hsu, Jiaming Xu, Xiaojun Lin, Mark R. Bell:
Integrating Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs. ITA 2018: 1-9 - [c22]Yudong Chen, Lili Su, Jiaming Xu:
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. SIGMETRICS (Abstracts) 2018: 96 - 2017
- [c21]Jess Banks, Cristopher Moore, Roman Vershynin, Nicolas Verzelen, Jiaming Xu:
Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization. ISIT 2017: 1137-1141 - 2016
- [c20]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Semidefinite Programs for Exact Recovery of a Hidden Community. COLT 2016: 1051-1095 - [c19]Elchanan Mossel, Jiaming Xu:
Density Evolution in the Degree-correlated Stochastic Block Model. COLT 2016: 1319-1356 - [c18]Elchanan Mossel, Jiaming Xu:
Local Algorithms for Block Models with Side Information. ITCS 2016: 71-80 - [c17]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Information limits for recovering a hidden community. ISIT 2016: 1894-1898 - [c16]Florent Krzakala, Jiaming Xu, Lenka Zdeborová:
Mutual information in rank-one matrix estimation. ITW 2016: 71-75 - 2015
- [c15]Yihong Wu, Jiaming Xu, Bruce E. Hajek:
Achieving exact cluster recovery threshold via semidefinite programming under the stochastic block model. ACSSC 2015: 1070-1074 - [c14]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Computational Lower Bounds for Community Detection on Random Graphs. COLT 2015: 899-928 - [c13]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Achieving exact cluster recovery threshold via semidefinite programming. ISIT 2015: 1442-1446 - [c12]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Exact recovery threshold in the binary censored block model. ITW Fall 2015: 99-103 - [c11]Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Collaboratively Learning Preferences from Ordinal Data. NIPS 2015: 1909-1917 - [c10]Rui Wu, Jiaming Xu, Rayadurgam Srikant, Laurent Massoulié, Marc Lelarge, Bruce E. Hajek:
Clustering and Inference From Pairwise Comparisons. SIGMETRICS 2015: 449-450 - 2014
- [c9]Jiaming Xu, Laurent Massoulié, Marc Lelarge:
Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results. COLT 2014: 903-920 - [c8]Yudong Chen, Jiaming Xu:
Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting. ICML 2014: 244-252 - [c7]Bruce E. Hajek, Sewoong Oh, Jiaming Xu:
Minimax-optimal Inference from Partial Rankings. NIPS 2014: 1475-1483 - [c6]Jiaming Xu, Rui Wu, Kai Zhu, Bruce E. Hajek, R. Srikant, Lei Ying:
Jointly clustering rows and columns of binary matrices: algorithms and trade-offs. SIGMETRICS 2014: 29-41 - 2013
- [c5]Marc Lelarge, Laurent Massoulié, Jiaming Xu:
Reconstruction in the labeled stochastic block model. ITW 2013: 1-5 - 2012
- [c4]Jiaming Xu, Bruce E. Hajek:
The supermarket game. ISIT 2012: 2511-2515 - 2011
- [c3]Jiaming Xu, Jeffrey G. Andrews, Syed Ali Jafar:
The net benefit of delayed finite-rate feedback in the MISO broadcast channel. Allerton 2011: 863-870 - [c2]Jiaming Xu, Jun Zhang, Jeffrey G. Andrews:
On the Accuracy of the Wyner Model in Downlink Cellular Networks. ICC 2011: 1-5 - 2010
- [c1]Jiaming Xu, Jun Zhang, Jeffrey G. Andrews:
When Does the Wyner Model Accurately Describe an Uplink Cellular Network? GLOBECOM 2010: 1-5
Informal and Other Publications
- 2024
- [i44]Xiaochun Niu, Lili Su, Jiaming Xu, Pengkun Yang:
Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms. CoRR abs/2409.04919 (2024) - 2023
- [i43]Lili Su, Jiaming Xu, Pengkun Yang:
Federated Learning in the Presence of Adversarial Client Unavailability. CoRR abs/2305.19971 (2023) - 2022
- [i42]Liren Yu, Jiaming Xu, Xiaojun Lin:
SeedGNN: Graph Neural Networks for Supervised Seeded Graph Matching. CoRR abs/2205.13679 (2022) - [i41]Lili Su, Jiaming Xu, Pengkun Yang:
Global Convergence of Federated Learning for Mixed Regression. CoRR abs/2206.07279 (2022) - [i40]Cheng Mao, Yihong Wu, Jiaming Xu, Sophie H. Yu:
Random graph matching at Otter's threshold via counting chandeliers. CoRR abs/2209.12313 (2022) - 2021
- [i39]Yihong Wu, Jiaming Xu, Sophie H. Yu:
Settling the Sharp Reconstruction Thresholds of Random Graph Matching. CoRR abs/2102.00082 (2021) - [i38]Jiaming Xu, Kuang Xu, Dana Yang:
Learner-Private Online Convex Optimization. CoRR abs/2102.11976 (2021) - [i37]Liren Yu, Jiaming Xu, Xiaojun Lin:
The Power of D-hops in Matching Power-Law Graphs. CoRR abs/2102.12975 (2021) - [i36]Jian Ding, Yihong Wu, Jiaming Xu, Dana Yang:
The planted matching problem: Sharp threshold and infinite-order phase transition. CoRR abs/2103.09383 (2021) - [i35]Jiaming Xu, Hanjing Zhu:
One-pass Stochastic Gradient Descent in Overparametrized Two-layer Neural Networks. CoRR abs/2105.00262 (2021) - [i34]Lili Su, Jiaming Xu, Pengkun Yang:
Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points. CoRR abs/2106.15216 (2021) - 2020
- [i33]Liren Yu, Jiaming Xu, Xiaojun Lin:
Graph Matching with Partially-Correct Seeds. CoRR abs/2004.03816 (2020) - 2019
- [i32]Jiaming Xu, Yuan Zhong:
Improved queue-size scaling for input-queued switches via graph factorization. CoRR abs/1903.00398 (2019) - [i31]Galen Reeves, Jiaming Xu, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Linear Regression. CoRR abs/1903.05046 (2019) - [i30]Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu:
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model. CoRR abs/1907.08880 (2019) - [i29]Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu:
Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality. CoRR abs/1907.08883 (2019) - [i28]Jiaming Xu, Dana Yang:
Optimal query complexity for private sequential learning. CoRR abs/1909.09836 (2019) - [i27]Jian Ding, Yihong Wu, Jiaming Xu, Dana Yang:
Consistent recovery threshold of hidden nearest neighbor graphs. CoRR abs/1911.08004 (2019) - [i26]Mehrdad Moharrami, Cristopher Moore, Jiaming Xu:
The Planted Matching Problem: Phase Transitions and Exact Results. CoRR abs/1912.08880 (2019) - [i25]Galen Reeves, Jiaming Xu, Ilias Zadik:
All-or-Nothing Phenomena: From Single-Letter to High Dimensions. CoRR abs/1912.13027 (2019) - 2018
- [i24]Vivek Kumar Bagaria, Jian Ding, David Tse, Yihong Wu, Jiaming Xu:
Hidden Hamiltonian Cycle Recovery via Linear Programming. CoRR abs/1804.05436 (2018) - [i23]Lili Su, Jiaming Xu:
Securing Distributed Machine Learning in High Dimensions. CoRR abs/1804.10140 (2018) - [i22]Yihong Wu, Jiaming Xu:
Statistical Problems with Planted Structures: Information-Theoretical and Computational Limits. CoRR abs/1806.00118 (2018) - [i21]Elchanan Mossel, Jiaming Xu:
Seeded Graph Matching via Large Neighborhood Statistics. CoRR abs/1807.10262 (2018) - [i20]Xiaodong Li, Yudong Chen, Jiaming Xu:
Convex Relaxation Methods for Community Detection. CoRR abs/1810.00315 (2018) - [i19]Jian Ding, Zongming Ma, Yihong Wu, Jiaming Xu:
Efficient random graph matching via degree profiles. CoRR abs/1811.07821 (2018) - 2017
- [i18]Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Learning from Comparisons and Choices. CoRR abs/1704.07228 (2017) - [i17]Yudong Chen, Lili Su, Jiaming Xu:
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent. CoRR abs/1705.05491 (2017) - 2016
- [i16]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Semidefinite Programs for Exact Recovery of a Hidden Community. CoRR abs/1602.06410 (2016) - [i15]Florent Krzakala, Jiaming Xu, Lenka Zdeborová:
Mutual Information in Rank-One Matrix Estimation. CoRR abs/1603.08447 (2016) - [i14]Jess Banks, Cristopher Moore, Roman Vershynin, Jiaming Xu:
Information-theoretic bounds and phase transitions in clustering, sparse PCA, and submatrix localization. CoRR abs/1607.05222 (2016) - 2015
- [i13]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions. CoRR abs/1502.07738 (2015) - [i12]Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Collaboratively Learning Preferences from Ordinal Data. CoRR abs/1506.07947 (2015) - [i11]Elchanan Mossel, Jiaming Xu:
Local Algorithms for Block Models with Side Information. CoRR abs/1508.02344 (2015) - [i10]Elchanan Mossel, Jiaming Xu:
Density Evolution in the Degree-correlated Stochastic Block Model. CoRR abs/1509.03281 (2015) - [i9]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Information Limits for Recovering a Hidden Community. CoRR abs/1509.07859 (2015) - [i8]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Recovering a Hidden Community Beyond the Spectral Limit in O(|E|log*|V|) Time. CoRR abs/1510.02786 (2015) - [i7]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Submatrix localization via message passing. CoRR abs/1510.09219 (2015) - [i6]Yudong Chen, Xiaodong Li, Jiaming Xu:
Convexified Modularity Maximization for Degree-corrected Stochastic Block Models. CoRR abs/1512.08425 (2015) - 2014
- [i5]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Computational Lower Bounds for Community Detection on Random Graphs. CoRR abs/1406.6625 (2014) - [i4]Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming. CoRR abs/1412.6156 (2014) - 2012
- [i3]Jiaming Xu, Bruce E. Hajek:
The Supermarket Game. CoRR abs/1202.2089 (2012) - 2011
- [i2]Jiaming Xu, Jeffrey G. Andrews, Syed Ali Jafar:
Broadcast Channels with Delayed Finite-Rate Feedback: Predict or Observe? CoRR abs/1105.3686 (2011) - 2010
- [i1]Jiaming Xu, Jun Zhang, Jeffrey G. Andrews:
On the Accuracy of the Wyner Model in Cellular Networks. CoRR abs/1009.5900 (2010)
Coauthor Index
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