12 citations · 13 across the 4 of their papers we have counts for
5 papers
Accelerated Consensus and Decentralized Optimization over Slowly Varying Networks
Darina Dvinskikh, Anton Novitskii, Demyan Yarmoshik +3
We study average consensus over slowly time-varying networks and its application to decentralized optimization. We introduce WAVE, a windowed Chebyshev method that limits the accum…
Decentralized Inexact Cubic Newton Method with Consensus Procedure
Artem Agafonov, Anton Novitskii, Alexander Rogozin +5
Distributed optimization is widely used in large-scale and privacy-preserving machine learning, where each agent stores a local objective and communicates only with its neighbors i…
Decentralized Proximal Optimization Method with Consensus Procedure
Alexander Rogozin, Anton Novitskii, Alexander Gasnikov
Decentralized optimization is well studied for smooth unconstrained problems. However, constrained problems or problems with composite terms are an open direction for research. We…
A General Framework for Distributed Partitioned Optimization
Savelii Chezhegov, Anton Novitskii, Alexander Rogozin +3
Decentralized optimization is widely used in large scale and privacy preserving machine learning and various distributed control and sensing systems. It is assumed that every agent…
The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems
Alexander Gasnikov, Anton Novitskii, Vasilii Novitskii +6
Gradient-free/zeroth-order methods for black-box convex optimization have been extensively studied in the last decade with the main focus on oracle calls complexity. In this paper,…