4 papers
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…