103 citations · 384 across the 41 of their papers we have counts for
5 papers · 2 filters
Solving Variational Inequalities with Monotone Operators on Domains Given by Linear Minimization Oracles
Anatoli Juditsky, Arkadi Nemirovski
The standard algorithms for solving large-scale convex-concave saddle point problems, or, more generally, variational inequalities with monotone operators, are proximal type algori…
Mirror Prox Algorithm for Multi-Term Composite Minimization and Semi-Separable Problems
Niao He, Anatoli Juditsky, Arkadi Nemirovski
In the paper, we develop a composite version of Mirror Prox algorithm for solving convex-concave saddle point problems and monotone variational inequalities of special structure, a…
On Lower Complexity Bounds for Large-Scale Smooth Convex Optimization
Cristobal Guzman, Arkadi Nemirovski
We derive lower bounds on the black-box oracle complexity of large-scale smooth convex minimization problems, with emphasis on minimizing smooth (with Holder continuous, with a giv…
Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski
Motivated by some applications in signal processing and machine learning, we consider two convex optimization problems where, given a cone , a norm and a smooth conv…
Dual subgradient algorithms for large-scale nonsmooth learning problems
Bruce Cox, Anatoli Juditsky, Arkadi Nemirovski
"Classical" First Order (FO) algorithms of convex optimization, such as Mirror Descent algorithm or Nesterov's optimal algorithm of smooth convex optimization, are well known to ha…