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Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction. (arXiv:2205.01608v1 [cs.LG])
Bilevel Optimization has witnessed notable progress recently with new
emerging efficient algorithms and has been applied to many machine learning
tasks such as data cleaning, few-shot learning, and neural architecture search.
However, little attention has been paid to solve the bilevel problems under
distributed setting. Federated learning (FL) is an emerging paradigm which
solves machine learning tasks over distributed-located data. FL problems are
challenging to solve due to the heterogeneity and communication bottleneck.
However, it is unclear how these challenges …