A survey of what to share in federated learning: perspectives on model utility, privacy leakage, and communication efficiency
Federated learning (FL) has emerged as a highly effective paradigm for privacy-preserving
collaborative training among different parties. Unlike traditional centralized learning, which …
collaborative training among different parties. Unlike traditional centralized learning, which …
Selective knowledge sharing for privacy-preserving federated distillation without a good teacher
While federated learning (FL) is promising for efficient collaborative learning without
revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high …
revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high …
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
Federated Learning (FL) is a distributed and privacy-preserving machine learning paradigm
that coordinates multiple clients to train a model while keeping the raw data localized …
that coordinates multiple clients to train a model while keeping the raw data localized …
KnFu: Effective Knowledge Fusion
SJ Seyedmohammadi, SK Atapour, J Abouei… - arXiv preprint arXiv …, 2024 - arxiv.org
Federated Learning (FL) has emerged as a prominent alternative to the traditional
centralized learning approach. Generally speaking, FL is a decentralized approach that …
centralized learning approach. Generally speaking, FL is a decentralized approach that …
Disclosure of Biology Teacher Technological Pedagogical Content Knowledge as an Indicator of Learning Quality in Jember, Indonesia
Understanding the quality of biology learning implemented by teachers in Jember is
essential to pay attention to. This study aims to identify biology teachers' technological …
essential to pay attention to. This study aims to identify biology teachers' technological …