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- Moscow Institute of Physics and TechnologyRU332 papers
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8 papers · 2 filters
Reconstruction of manifold embeddings into Euclidean spaces via intrinsic distances
Nikita Puchkin, Vladimir Spokoiny, Eugene Stepanov +1
We consider the problem of reconstructing an embedding of a compact connected Riemannian manifold in a Euclidean space up to an almost isometry, given the information on intrinsic…
Recent theoretical advances in decentralized distributed convex optimization
Eduard Gorbunov, Alexander Rogozin, Aleksandr Beznosikov +2
In the last few years, the theory of decentralized distributed convex optimization has made significant progress. The lower bounds on communications rounds and oracle calls have ap…
Zeroth-Order Algorithms for Smooth Saddle-Point Problems
Abdurakhmon Sadiev, Aleksandr Beznosikov, Pavel Dvurechensky +1
Saddle-point problems have recently gained increased attention from the machine learning community, mainly due to applications in training Generative Adversarial Networks using sto…
Linearly Convergent Gradient-Free Methods for Minimization of Parabolic Approximation
Aleksandra Bazarova, Aleksandr Beznosikov, Alexander Gasnikov
Finding the global minimum of non-convex functions is one of the main and most difficult problems in modern optimization. In the first part of the paper, we consider a certain clas…
Finding Equilibria in the Traffic Assignment Problem with Primal-Dual Gradient Methods for Stable Dynamics Model and Beckmann Model
Meruza Kubentayeva, Alexander Gasnikov
In this paper we consider the application of several gradient methods to the traffic assignment problem: we search equilibria in the stable dynamics model (Nesterov and De Palma, 2…
Gradient-Free Methods for Saddle-Point Problem
Aleksandr Beznosikov, Abdurakhmon Sadiev, Alexander Gasnikov
In the paper, we generalize the approach Gasnikov et. al, 2017, which allows to solve (stochastic) convex optimization problems with an inexact gradient-free oracle, to the convex-…