1 citations · 1 across the 12 of their papers we have counts for
Showing 2024 · cs.LGShow all
3 papers · 2 filters
cs.LG2024
Personalized Federated Learning Techniques: Empirical Analysis
Azal Ahmad Khan, Ahmad Faraz Khan, Haider Ali +1
Personalized Federated Learning (pFL) holds immense promise for tailoring machine learning models to individual users while preserving data privacy. However, achieving optimal perf…
cs.LG2024
DynamicFL: Federated Learning with Dynamic Communication Resource Allocation
Qi Le, Enmao Diao, Xinran Wang +3
Federated Learning (FL) is a collaborative machine learning framework that allows multiple users to train models utilizing their local data in a distributed manner. However, consid…
cs.LG2024★ 1 cited
ColA: Collaborative Adaptation with Gradient Learning
Enmao Diao, Qi Le, Suya Wu +4
A primary function of back-propagation is to compute both the gradient of hidden representations and parameters for optimization with gradient descent. Training large models requir…