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Alexandre Tsybakov

2 accepted papers

2022

A gradient estimator via L1-randomization for online zero-order optimization with two point feedback

NeurIPS 2022accept

This work studies online zero-order optimization of convex and Lipschitz functions. We present a novel gradient estimator based on two function evaluations and randomization on the $\ell_1$-sphere. Considering different geometries of feasible sets and Lipschitz assumptions we analyse online dual av…

Cited by 30SourcePDFScholar
2020

Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits

NeurIPS 2020poster

We address the problem of zero-order optimization of a strongly convex function. The goal is to find the minimizer of the function by a sequential exploration of its function values, under measurement noise. We study the impact of higher order smoothness properties of the function on the optimizatio…

Cited by 60SourcePDFScholar