2 citations · 7 across the 20 of their papers we have counts for
25 papers
Decentralised convex optimisation with probability-proportional-to-size quantization
Dmitrii Pasechniuk, Pavel Dvurechensky, César A. Uribe +1
Communication is one of the bottlenecks of distributed optimisation and learning. To overcome this bottleneck, we propose a novel quantization method that transforms a vector into…
OPTAMI: Global Superlinear Convergence of High-order Methods
Dmitry Kamzolov, Dmitry Pasechnyuk, Artem Agafonov +2
Second-order methods for convex optimization outperform first-order methods in terms of theoretical iteration convergence, achieving rates up to for highly-smooth funct…
Algorithms for Euclidean-regularised Optimal Transport
Dmitry A. Pasechnyuk, Michael Persiianov, Pavel Dvurechensky +1
This paper addresses the Optimal Transport problem, which is regularized by the square of Euclidean -norm. It offers theoretical guarantees regarding the iteration complexi…
Primal-Dual Gradient Methods for Searching Network Equilibria in Combined Models with Nested Choice Structure and Capacity Constraints
Meruza Kubentayeva, Demyan Yarmoshik, Mikhail Persiianov +8
We consider a network equilibrium model (i.e. a combined model), which was proposed as an alternative to the classic four-step approach for travel forecasting in transportation net…
Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula
Kirill Brilliantov, Fedor Pavutnitskiy, Dmitry Pasechnyuk +1
Computing homotopy groups of spheres has long been a fundamental objective in algebraic topology. Various theoretical and algorithmic approaches have been developed to tackle this…
A randomised non-descent method for global optimisation
Dmitry A. Pasechnyuk, Alexander Gornov
This paper proposes novel algorithm for non-convex multimodal constrained optimisation problems. It is based on sequential solving restrictions of problem to sections of feasible s…