Xin Zhang

activity

20192026

most citedByzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach

9 citations · 26 across the 12 of their papers we have counts for

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Showing 2022Show all

3 papers · 1 filter

cs.LG2022

SAGDA: Achieving $O (ε^{- 2})$ Communication Complexity in Federated Min-Max Learning

Haibo Yang, Zhuqing Liu, Xin Zhang +1

To lower the communication complexity of federated min-max learning, a natural approach is to utilize the idea of infrequent communications (through multiple local updates) same as…

cs.LG2022

SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters

Zhuqing Liu, Xin Zhang, Jia Liu

To increase the training speed of distributed learning, recent years have witnessed a significant amount of interest in developing both synchronous and asynchronous distributed sto…

cs.LG2022★ 1 cited

INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks

Zhuqing Liu, Xin Zhang, Prashant Khanduri +2

In recent years, decentralized bilevel optimization problems have received increasing attention in the networking and machine learning communities thanks to their versatility in mo…

SAGDA: Achieving O(ε−2) Communication Complexity in Federated Min-Max Learning

SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters

INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks

SAGDA: Achieving $O (ε^{- 2})$ Communication Complexity in Federated Min-Max Learning