4 citations · 6 across the 2 of their papers we have counts for
7 papers
Near-Optimal Procedures for Model Discrimination with Non-Disclosure Properties
Dmitrii M. Ostrovskii, Mohamed Ndaoud, Adel Javanmard +1
Let be the population risk minimizers associated to some loss and two distributions $\mathbb{P}_0,\mat…
Efficient Primal-Dual Algorithms for Large-Scale Multiclass Classification
Dmitry Babichev, Dmitrii Ostrovskii, Francis Bach
We develop efficient algorithms to train -regularized linear classifiers with large dimensionality of the feature space, number of classes , and sample size . Our…
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions
Dmitrii Ostrovskii, Alessandro Rudi
In this work we provide an estimator for the covariance matrix of a heavy-tailed multivariate distributionWe prove that the proposed estimator admits an \tex…
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance
Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis Bach +1
We consider learning methods based on the regularization of a convex empirical risk by a squared Hilbertian norm, a setting that includes linear predictors and non-linear predictor…
Finite-sample analysis of M-estimators using self-concordance
Dmitrii Ostrovskii, Francis Bach
The classical asymptotic theory for parametric -estimators guarantees that, in the limit of infinite sample size, the excess risk has a chi-square type distribution, even in the…
Adaptive Denoising of Signals with Local Shift-Invariant Structure
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski +1
We discuss the problem of adaptive discrete-time signal denoising in the situation where the signal to be recovered admits a "linear oracle" -- an unknown linear estimate that take…