Federated Learning | Remy Sun

Buobe IA context · why it matters

Models train locally before syncing with central server — Ensures privacy while allowing for model improvement.
Large conflicts between client updates can degrade performance — Need to develop better aggregation methods to maintain model quality during federated learning.

Published by

remysun.github.io

on •1 min read

Federated Learning studies how models can be trained without a centralized dataset through the cooperation of multiple clients that each posess their own private dataset.

Deep Learning Federated Learning

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