25 citations · 60 across the 4 of their papers we have counts for
4 papers
Sparse recovery by reduced variance stochastic approximation
Anatoli Juditsky, Andrei Kulunchakov, Hlib Tsyntseus
In this paper, we discuss application of iterative Stochastic Optimization routines to the problem of sparse signal recovery from noisy observation. Using Stochastic Mirror Descent…
A Generic Acceleration Framework for Stochastic Composite Optimization
Andrei Kulunchakov, Julien Mairal
In this paper, we introduce various mechanisms to obtain accelerated first-order stochastic optimization algorithms when the objective function is convex or strongly convex. Specif…
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
Andrei Kulunchakov, Julien Mairal
In this paper, we propose a unified view of gradient-based algorithms for stochastic convex composite optimization by extending the concept of estimate sequence introduced by Neste…
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise
Andrei Kulunchakov, Julien Mairal
In this paper, we propose a unified view of gradient-based algorithms for stochastic convex composite optimization by extending the concept of estimate sequence introduced by Neste…