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- W3208305611 abstract "We study a variant of online optimization in which the learner receives k-rounddelayed feedback about hitting cost and there is a multi-step nonlinear switching cost, i.e., costs depend on multiple previous actions in a nonlinear manner. Our main result shows that a novel Iterative Regularized Online Balanced Descent (iROBD) algorithm has a constant, dimension-free competitive ratio that is $O(L^2k )$, where L is the Lipschitz constant of the switching cost. Additionally, we provide lower bounds that illustrate the Lipschitz condition is required and the dependencies on k and L are tight. Finally, via reductions, we show that this setting is closely related to online control problems with delay, nonlinear dynamics, and adversarial disturbances, where iROBD directly offers constant-competitive online policies." @default.
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- W3208305611 date "2022-02-24" @default.
- W3208305611 modified "2023-10-10" @default.
- W3208305611 title "Online Optimization with Feedback Delay and Nonlinear Switching Cost" @default.
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- W3208305611 doi "https://doi.org/10.1145/3508037" @default.
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