Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. (arXiv:2206.10870v1 [stat.ML])

Web: http://arxiv.org/abs/2206.10870

Bilevel optimization have gained growing interests, with numerous
applications found in meta learning, minimax games, reinforcement learning, and
nested composition optimization. This paper studies the problem of distributed
bilevel optimization over a network where agents can only communicate with
neighbors, including examples from multi-task, multi-agent learning and
federated learning. In this paper, we propose a gossip-based distributed
bilevel learning algorithm that allows networked agents to solve both the inner
and outer optimization problems in a single timescale and share information …

arxiv communication decentralized ml networks optimization stochastic