26 citations · 56 across the 14 of their papers we have counts for
4 papers · 1 filter
Learn How to Query from Unlabeled Data Streams in Federated Learning
Yuchang Sun, Xinran Li, Tao Lin +1
Federated learning (FL) enables collaborative learning among decentralized clients while safeguarding the privacy of their local data. Existing studies on FL typically assume offli…
Exploring Selective Layer Fine-Tuning in Federated Learning
Yuchang Sun, Yuexiang Xie, Bolin Ding +2
Federated learning (FL) has emerged as a promising paradigm for fine-tuning foundation models using distributed data in a privacy-preserving manner. Under limited computational res…
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Xiaolu Wang, Yuchang Sun, Hoi-To Wai +1
We consider the distributed learning problem with data dispersed across multiple workers under the orchestration of a central server. Asynchronous Stochastic Gradient Descent (SGD)…
How to Collaborate: Towards Maximizing the Generalization Performance in Cross-Silo Federated Learning
Yuchang Sun, Marios Kountouris, Jun Zhang
Federated learning (FL) has attracted vivid attention as a privacy-preserving distributed learning framework. In this work, we focus on cross-silo FL, where clients become the mode…