8 citations · 25 across the 12 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…