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Dong Quan Vu

2 accepted papers

2022

UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

ICML 2022oral

Universal methods achieve optimal convergence rate guarantees in convex optimization without any prior knowledge of the problem’s regularity parameters or the attributes of the gradient oracle employed by the method. In this regard, existing state-of-the-art algorithms achieve an $O(1/T^2)$ converge…

2021

Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights

NeurIPS 2021poster

We examine an adaptive learning framework for nonatomic congestion games where the players' cost functions may be subject to exogenous fluctuations (e.g., due to disturbances in the network, variations in the traffic going through a link). In this setting, the popular multiplicative/ exponential wei…

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