Author

Dmitrii M. Ostrovskii

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Jul 2026

Bandit PCA with Minimax Optimal Regret

An adaptive adversary is constructed that refines a hidden large-reward subspace based on the learner's actions, in such a way that low regret is impossible without estimating the subspace; as a result, lower-bounding the regret reduces to studying the arising subspace estimation problem.

Moise Blanchard, Dmitrii M. Ostrovskii, Aadirupa Saha · arXiv.org · 0 citations

Jul 2026

Entropy-Smooth Convex Optimization Cannot Be Accelerated

We prove an $\Omega(L/T)$ lower bound for the convergence rate of minimization in the class of functions that are convex and $L$-smooth relative to negative entropy on the standard $d$-simplex, valid for every first-order method when $d = \Omega(T^2)$. In particular, this shows that mirror descent is optimal up to a lo...

Jacob M. Aguirre, Dmitrii M. Ostrovskii · arXiv.org · 0 citations