Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
Abstract
This paper introduces online bilevel optimization in which a sequence of time-varying bilevel problems is revealed one after the other. We extend the known regret bounds for online single-level algorithms to the bilevel setting. Specifically, we provide new notions of bilevel regret, develop an online alternating time-averaged gradient method that is capable of leveraging smoothness, and give regret bounds in terms of the path-length of the inner and outer minimizer sequences.
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