8 citations · 25 across the 12 of their papers we have counts for
12 papers
Stochastic Optimization and Data Science
Arutyun Avetisyan, Darina Dvinskikh, Alexander Gasnikov +3
This paper aims to motivate stochastic optimization problems from a statistical perspective and a statistical learning perspective, where the goal is to maximize the log-likelihood…
On weak greedy algorithms
A. S. Spivak, V. N. Temlyakov
The main goal of this paper is twofold. First, we extend some results known in the case of weak greedy algorithms with a scalar parameter to the case of weak greedy algorithms with…
On stability of Weak Greedy Algorithm in the presence of noise
V. N. Temlyakov
This paper is devoted to the theoretical study of the efficiency, namely, stability of some greedy algorithms. In the greedy approximation theory researchers are mostly interested…
Brief introduction in greedy approximation
V. Temlyakov
Sparse approximation is important in many applications because of concise form of an approximant and good accuracy guarantees. The theory of compressed sensing, which proved to be…
On greedy approximation in complex Banach spaces
A. Gasnikov, V. Temlyakov
The general theory of greedy approximation with respect to arbitrary dictionaries is well developed in the case of real Banach spaces. Recently, some of results proved for the Weak…
Bounds for the sampling discretization error and their applications to the universal sampling discretization
E. D. Kosov, V. N. Temlyakov
In the first part of the paper we study absolute error of sampling discretization of the integral -norm for function classes of continuous functions. We use basic approaches f…
Sampling discretization of the uniform norm and applications
E. D. Kosov, V. N. Temlyakov
Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. Previous known results show that for any -dimensiona…
Rate of convergence of Thresholding Greedy Algorithms
V. N. Temlyakov
The rate of convergence of the classical Thresholding Greedy Algorithm with respect to bases is studied in this paper. We bound the error of approximation by the product of both no…
Universal discretization and sparse sampling recovery
F. Dai, V. Temlyakov
Recently, it was discovered that for a given function class the error of best linear recovery in the square norm can be bounded above by the Kolmogorov width of $\math…
Some improved bounds in sampling discretization of integral norms
F. Dai, E. Kosov, V. Temlyakov
The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization…
Sampling discretization error of integral norms for function classes with small smoothness
V. N. Temlyakov
We consider infinitely dimensional classes of functions and instead of the relative error setting, which was used in previous papers on the integral norm discretization, we conside…
Some Topics in Fourier Analysis and Approximation Theory
R. M. Trigub
This manuscript presents shortly the results obtained by participants of the scientific seminar which is held more than twenty years under leadership of the author at Donetsk Unive…