Optimizing Split Points for Error-Resilient SplitFed Learning

no code implementations • 29 May 2024 • Chamani Shiranthika, Parvaneh Saeedi, Ivan V. Bajić

Recent advancements in decentralized learning, such as Federated Learning (FL), Split Learning (SL), and Split Federated Learning (SplitFed), have expanded the potentials of machine learning.

Federated Learning Image Segmentation +1

SplitFed resilience to packet loss: Where to split, that is the question

no code implementations • 25 Jul 2023 • Chamani Shiranthika, Zahra Hafezi Kafshgari, Parvaneh Saeedi, Ivan V. Bajić

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 (SplitFed or SFL).

Federated Learning

Quality-Adaptive Split-Federated Learning for Segmenting Medical Images with Inaccurate Annotations

no code implementations • 28 Apr 2023 • Zahra Hafezi Kafshgari, Chamani Shiranthika, Parvaneh Saeedi, Ivan V. Bajić

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.

Federated Learning Image Segmentation +2