14 citations · 16 across the 10 of their papers we have counts for
14 papers
Scalable Cox Regression via Grouped Risk Sets and Sharper LogSumExp Rates
Elizaveta Iashchinskaia, Egor Gladin
Motivated by the computational challenges of large-scale Cox regression, we study stochastic minimization of LogSumExp objectives over large sets. Mini-batch normalizer estimates g…
Boundary Geometry and Global Rates of Cyclic Coordinate Descent for SVM Duals
Egor Gladin, Eva Ibodova
Cyclic coordinate descent is widely used to train support vector machines, but global linear convergence alone gives limited guidance about the rate on a particular instance. We st…
Clipped or Unclipped? Finite-Sample Trade-offs for Averaged SGD under Heavy-Tailed Noise
Alexandra Suvorikova, Egor Gladin, Darina Dvinskikh +5
Gradient clipping is widely used to stabilize training, but it need not improve the statistical accuracy of averaged SGD, even under heavy-tailed noise. We derive a finite-sample c…
Sampled-Max Subgradient Method for Convex Finite-Max Optimization
Egor Gladin, Anna Popova, Georgii Babinskii
We study the Sampled-Max Subgradient Method (SMax-SGM) for large convex finite-max problems. Each iteration maximizes over a fresh random subset of the components and takes one…
Mathematical methods of reinforcement learning
Denis Belomestny, Alexander Gasnikov, Egor Gladin +5
Reinforcement learning (RL) is increasingly grounded in tools from probability, optimization, and operator theory. This survey organizes the mathematical structures that underpin t…
Improved Stochastic Optimization of LogSumExp
Egor Gladin, Alexey Kroshnin, Jia-Jie Zhu +1
The LogSumExp function, dual to the Kullback-Leibler (KL) divergence, plays a central role in many important optimization problems, including entropy-regularized optimal transport…
Interaction-Force Transport Gradient Flows
Egor Gladin, Pavel Dvurechensky, Alexander Mielke +1
This paper presents a new gradient flow dissipation geometry over non-negative and probability measures. This is motivated by a principled construction that combines the unbalanced…
Accuracy Certificates for Convex Minimization with Inexact Oracle
Egor Gladin, Alexander Gasnikov, Pavel Dvurechensky
Accuracy certificates for convex minimization problems allow for online verification of the accuracy of approximate solutions and provide a theoretically valid online stopping crit…
Algorithm for Constrained Markov Decision Process with Linear Convergence
Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina +3
The problem of constrained Markov decision process is considered. An agent aims to maximize the expected accumulated discounted reward subject to multiple constraints on its costs…
Vaidya's method for convex stochastic optimization in small dimension
Egor Gladin, Alexander Gasnikov, Elena Ermakova
This paper considers a general problem of convex stochastic optimization in a relatively low-dimensional space (e.g., 100 variables). It is known that for deterministic convex opti…
Solving smooth min-min and min-max problems by mixed oracle algorithms
Egor Gladin, Abdurakhmon Sadiev, Alexander Gasnikov +3
In this paper, we consider two types of problems that have some similarity in their structure, namely, min-min problems and min-max saddle-point problems. Our approach is based on…
On solving convex min-min problems with smoothness and strong convexity in one variable group and small dimension of the other
Egor Gladin, Mohammad Alkousa, Alexander Gasnikov
This paper is devoted to some approaches for convex min-min problems with smoothness and strong convexity in only one of the two variable groups. It is shown that the proposed appr…
Ellipsoid method for convex stochastic optimization in small dimension
Egor Gladin, Karina Zaynullina
The article considers minimization of the expectation of convex function. Problems of this type often arise in machine learning and a number of other applications. In practice, sto…
Solving strongly convex-concave composite saddle point problems with a small dimension of one of the variables
Egor Gladin, Ilya Kuruzov, Fedor Stonyakin +3
The article is devoted to the development of algorithmic methods ensuring efficient complexity bounds for strongly convex-concave saddle point problems in the case when one of the…