Recent Posts

A new article about random proximal subspace method with identification-based sampling

Title: Adaptive Catalyst for smooth convex optimization Together with Anastasiya Ivanova, Egor Shulgin, and Alexander Gasnikov from …

Talk of Nikita Doikov

Hello everyone, On Monday, $23^{\text{rd}}$ September Nikita Doikov will give a talk about some recent results on accelerated proximal …

Recent & Upcoming Talks

Identification-Based First-Order Algorithms for Distributed Learning

In this talk, we present a first-order optimization algorithm for distributed learning problems. We propose an efficient sparsification …

Distributed First-Order Optimization with Tamed Communications

Many machine learning and signal processing applications involve high-dimensional nonsmooth optimization problems. The nonsmoothness is …

Identify and Sparsify$:$ Distributed Optimization with Asynchronous Moderate Communications

We present an asynchronous optimization algorithm for distributed learning, that efficiently reduces the communications between a …

Identify and Sparsify$:$ Distributed Optimization with Asynchronous Moderate Communications

We present an asynchronous optimization algorithm for distributed learning, that efficiently reduces the communications between a …

Distributed Optimization with Sparse Communications and Structure Identification

We propose an efficient distributed algorithm for solving regularized learning problems. In a distributed framework with a master …

Recent Publications

Many applications in machine learning or signal processing involve nonsmooth optimization problems. This nonsmoothness brings a …

Adaptive Catalyst for smooth convex optimization

In this paper, we present the generic framework that allows accelerating almost arbitrary non-accelerated deterministic and randomized …

Asynchronous Distributed Learning with Sparse Communications and Identification

In this paper, we present an asynchronous optimization algorithm for distributed learning, that efficiently reduces the communications …

A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion

In this work we present a randomized gossip algorithm for solving the average consensus problem while at the same time protecting the …

Privacy Preserving Randomized Gossip Algorithms

In this work we present a randomized gossip algorithm for solving the average consensus problem while at the same time protecting the …

Teaching

Optimisation Numérique

Basic course on numerical optimization (theory and implementation)

Refresher course$:$ Numerical Matrix Analysis and Optimization

This short course focuses on matrix analysis and optimization

Optimisation Numérique

Basic course on numerical optimization (theory and implementation)

Convex and Distributed Optimization

Incremental and Stochastic Optimization for Learning, Spark, Distributed Optimization.

Refresher course$:$ Numerical Matrix Analysis and Optimization

This short course focuses on matrix analysis and optimization

Experience

Université Grenoble Alpes

Sep 2018 – Present Grenoble, France

2019 - 2020

• Matrix Analysis and Numerical Optimization

• Numerical Optimization

2018 - 2019

• Matrix Analysis and Numerical Optimization

• Convex and Distributed Optimization

• Numerical Optimization

Altium

Jan 2016 – Sep 2017 Moscow, Russia

Citibank

Jul 2014 – Feb 2015 Moscow, Russia

Higher School of Economics

Sep 2013 – Jun 2015 Moscow, Russia
• Calculus