Xin Zhang
Orcid: 0000-0002-0784-2038Affiliations:
- Iowa State University, Department of Statistics, Ames, IA, USA (PhD 2021)
According to our database1,
Xin Zhang
authored at least 22 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
IEEE Trans. Inf. Forensics Secur., 2024
2023
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities.
Proceedings of the Twenty-fourth International Symposium on Theory, 2023
2022
Fast and Robust Sparsity Learning Over Networks: A Decentralized Surrogate Median Regression Approach.
IEEE Trans. Signal Process., 2022
SAGDA: Achieving O(ε<sup>-2</sup>) Communication Complexity in Federated Min-Max Learning.
CoRR, 2022
SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data.
Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022
SYNTHESIS: a semi-asynchronous path-integrated stochastic gradient method for distributed learning in computing clusters.
Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022
INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks.
Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022
Proceedings of the International Conference on Machine Learning, 2022
2021
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning.
Proceedings of the MobiHoc '21: The Twenty-second International Symposium on Theory, 2021
Low Sample and Communication Complexities in Decentralized Learning: A Triple Hybrid Approach.
Proceedings of the 40th IEEE Conference on Computer Communications, 2021
2020
Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization.
Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020
Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach.
Proceedings of the Mobihoc '20: The Twenty-first ACM International Symposium on Theory, 2020
Communication-Efficient Network-Distributed Optimization with Differential-Coded Compressors.
Proceedings of the 39th IEEE Conference on Computer Communications, 2020
Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020
2019
Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach.
CoRR, 2019
Compressed Distributed Gradient Descent: Communication-Efficient Consensus over Networks.
Proceedings of the 2019 IEEE Conference on Computer Communications, 2019
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
2017
Comput. Biol. Chem., 2017
2013
J. Networks, 2013