Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization

DOI10.1109/TSP.2021.3092377MaRDI QIDQ5868746

Wotao Yin, Tianyi Chen, Yuejiao Sun

Publication date: 23 September 2022

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.10847

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

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Learning with Limited Samples: Meta-Learning and Applications to Communication Systems ⋮ Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates ⋮ Probability maximization via Minkowski functionals: convex representations and tractable resolution ⋮ Hybrid SGD algorithms to solve stochastic composite optimization problems with application in sparse portfolio selection problems ⋮ An Improved Unconstrained Approach for Bilevel Optimization ⋮ Stochastic composition optimization of functions without Lipschitz continuous gradient ⋮ Distributed stochastic compositional optimization problems over directed networks ⋮ A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning

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