9 citations · 24 across the 11 of their papers we have counts for
7 papers · 1 filter
FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation
Minghui Chen, Meirui Jiang, Qi Dou +2
Cross-silo federated learning (FL) enables the development of machine learning models on datasets distributed across data centers such as hospitals and clinical research laboratori…
Scalable Data Point Valuation in Decentralized Learning
Konstantin D. Pandl, Chun-Yin Huang, Ivan Beschastnikh +3
Existing research on data valuation in federated and swarm learning focuses on valuing client contributions and works best when data across clients is independent and identically d…
Federated Learning on Virtual Heterogeneous Data with Local-global Distillation
Chun-Yin Huang, Ruinan Jin, Can Zhao +2
While Federated Learning (FL) is gaining popularity for training machine learning models in a decentralized fashion, numerous challenges persist, such as asynchronization, computat…
A Convergence Theory for Federated Average: Beyond Smoothness
Xiaoxiao Li, Zhao Song, Runzhou Tao +1
Federated learning enables a large amount of edge computing devices to learn a model without data sharing jointly. As a leading algorithm in this setting, Federated Average FedAvg,…
FedMT: Federated Learning with Mixed-type Labels
Qiong Zhang, Jing Peng, Xin Zhang +3
In federated learning (FL), classifiers (e.g., deep networks) are trained on datasets from multiple data centers without exchanging data across them, which improves the sample effi…
Federated Adversarial Learning: A Framework with Convergence Analysis
Xiaoxiao Li, Zhao Song, Jiaming Yang
Federated learning (FL) is a trending training paradigm to utilize decentralized training data. FL allows clients to update model parameters locally for several epochs, then share…
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features
Meirui Jiang, Xiaoxiao Li, Xiaofei Zhang +2
How to tackle non-iid data is a crucial topic in federated learning. This challenging problem not only affects training process, but also harms performance of clients not participa…