3 papers
cs.LG2024
SplitFedZip: Learned Compression for Data Transfer Reduction in Split-Federated Learning
Chamani Shiranthika, Hadi Hadizadeh, Parvaneh Saeedi +1
Federated Learning (FL) enables multiple clients to train a collaborative model without sharing their local data. Split Learning (SL) allows a model to be trained in a split manner…
cs.CV2023
SplitFed resilience to packet loss: Where to split, that is the question
Chamani Shiranthika, Zahra Hafezi Kafshgari, Parvaneh Saeedi +1
Decentralized machine learning has broadened its scope recently with the invention of Federated Learning (FL), Split Learning (SL), and their hybrids like Split Federated Learning…
cs.CV2023
Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations
Zahra Hafezi Kafshgari, Chamani Shiranthika, Parvaneh Saeedi +1
SplitFed Learning, a combination of Federated and Split Learning (FL and SL), is one of the most recent developments in the decentralized machine learning domain. In SplitFed learn…