On Approximate Recovery of Functions with Bounded Mixed Derivative. - Vladimir N. Temlyakov (J. Complex., 1993)

An Inequality for Trigonometric Polynomials and Its Application for Estimating the Entropy Numbers. - Vladimir N. Temlyakov (J. Complex., 1995)

Some remarks on greedy algorithms. - Ronald A. DeVore; Vladimir N. Temlyakov (Adv. Comput. Math., 1996)

Nonlinear Approximation in Finite-Dimensional Spaces. - Ronald A. DeVore; Vladimir N. Temlyakov (J. Complex., 1997)

The best m-term approximation and greedy algorithms. - Vladimir N. Temlyakov (Adv. Comput. Math., 1998)

Weak greedy algorithms. - Vladimir N. Temlyakov (Adv. Comput. Math., 2000)

Greedy algorithms in Banach spaces. - Vladimir N. Temlyakov (Adv. Comput. Math., 2001)

A Criterion for Convergence of Weak Greedy Algorithms. - Vladimir N. Temlyakov (Adv. Comput. Math., 2002)

Best Basis Selection for Approximation in Lp. - Ronald A. DeVore; Guergana Petrova; Vladimir N. Temlyakov (Found. Comput. Math., 2003)

Nonlinear Methods of Approximation. - Vladimir N. Temlyakov (Found. Comput. Math., 2003)

Vector greedy algorithms. - Adam Lutoborski; Vladimir N. Temlyakov (J. Complex., 2003)

Cubature formulas, discrepancy, and nonlinear approximation. - Vladimir N. Temlyakov (J. Complex., 2003)

Simultaneous greedy approximation in Banach spaces. - Dany Leviatan; Vladimir N. Temlyakov (J. Complex., 2005)

Universal Algorithms for Learning Theory Part I : Piecewise Constant Functions. - Peter Binev; Albert Cohen 002; Wolfgang Dahmen; Ronald A. DeVore; Vladimir N. Temlyakov (J. Mach. Learn. Res., 2005)

Simultaneous approximation by greedy algorithms. - Dany Leviatan; Vladimir N. Temlyakov (Adv. Comput. Math., 2006)

Approximation Methods for Supervised Learning. - Ronald A. DeVore; Gerard Kerkyacharian; Dominique Picard; Vladimir N. Temlyakov (Found. Comput. Math., 2006)

Stable recovery of sparse overcomplete representations in the presence of noise. - David L. Donoho; Michael Elad; Vladimir N. Temlyakov (IEEE Trans. Inf. Theory, 2006)

Greedy expansions in Banach spaces. - Vladimir N. Temlyakov (Adv. Comput. Math., 2007)

On Lebesgue-type inequalities for greedy approximation. - David L. Donoho; Michael Elad; Vladimir N. Temlyakov (J. Approx. Theory, 2007)

Greedy approximation with regard to non-greedy bases. - Vladimir N. Temlyakov; Mingrui Yang; Peixin Ye (Adv. Comput. Math., 2011)

On the size of incoherent systems. - J. L. Nelson; Vladimir N. Temlyakov (J. Approx. Theory, 2011)

On performance of greedy algorithms. - Vladimir N. Temlyakov; Pavel Zheltov (J. Approx. Theory, 2011)

Super greedy type algorithms. - Entao Liu; Vladimir N. Temlyakov (Adv. Comput. Math., 2012)

Fibonacci sets and symmetrization in discrepancy theory. - Dmitriy Bilyk; Vladimir N. Temlyakov; Rui Yu (J. Complex., 2012)

The Orthogonal Super Greedy Algorithm and Applications in Compressed Sensing. - Entao Liu; Vladimir N. Temlyakov (IEEE Trans. Inf. Theory, 2012)

An inequality for the entropy numbers and its application. - Vladimir N. Temlyakov (J. Approx. Theory, 2013)

Lebesgue-Type Inequalities for Greedy Approximation in Banach Spaces. - Daniel Savu; Vladimir N. Temlyakov (IEEE Trans. Inf. Theory, 2013)

Greedy algorithms in convex optimization on Banach spaces. - Vladimir N. Temlyakov (ACSSC, 2014)

Incremental Greedy Algorithm and Its Applications in Numerical Integration. - Vladimir N. Temlyakov (MCQMC, 2014)

Sparse Approximation and Recovery by Greedy Algorithms. - Eugene D. Livshitz; Vladimir N. Temlyakov (IEEE Trans. Inf. Theory, 2014)

Nonlinear tensor product approximation of functions. - Daurenbek Bazarkhanov; Vladimir N. Temlyakov (J. Complex., 2015)

Convex Optimization on Banach Spaces. - Ronald A. DeVore; Vladimir N. Temlyakov (Found. Comput. Math., 2016)

On the entropy numbers of the mixed smoothness function classes. - Vladimir N. Temlyakov (J. Approx. Theory, 2017)

Universal discretization. - Vladimir N. Temlyakov (J. Complex., 2018)

Smooth fixed volume discrepancy, dispersion, and related problems. - Vladimir N. Temlyakov (J. Approx. Theory, 2019)

Sampling discretization error of integral norms for function classes. - Vladimir N. Temlyakov (J. Complex., 2019)

Biorthogonal greedy algorithms in convex optimization. - Anton Dereventsov; Vladimir N. Temlyakov (CoRR, 2020)

Sampling discretization of integral norms. - Feng Dai; Andriy Prymak; A. Shadrin; Vladimir N. Temlyakov; S. Yu. Tikhonov (CoRR, 2020)

On the fixed volume discrepancy of the Korobov point sets. - A. S. Rubtsova; K. S. Ryutin; Vladimir N. Temlyakov (CoRR, 2020)

Numerical integration without smoothness assumption. - Vladimir N. Temlyakov (CoRR, 2020)

Sampling discretization of integral norms of the hyperbolic cross polynomials. - Vladimir N. Temlyakov (CoRR, 2020)

A remark on entropy numbers. - Vladimir N. Temlyakov (CoRR, 2020)

On sampling discretization in L2. - Irina V. Limonova; Vladimir N. Temlyakov (CoRR, 2020)

On optimal recovery in L2. - Vladimir N. Temlyakov (CoRR, 2020)

Sparse approximation of individual functions. - Leyla Burusheva; Vladimir N. Temlyakov (J. Approx. Theory, 2020)

On the fixed volume discrepancy of the Fibonacci sets in the integral norms. - Vladimir N. Temlyakov; Mario Ullrich (J. Complex., 2020)

A remark on discretization of the uniform norm. - Boris S. Kashin; Vladimir N. Temlyakov (CoRR, 2021)

Universal sampling discretization. - Feng Dai; Vladimir N. Temlyakov (CoRR, 2021)

Sampling discretization of integral norms and its application. - Feng Dai; Vladimir N. Temlyakov (CoRR, 2021)

On optimal recovery in L2. - Vladimir N. Temlyakov (J. Complex., 2021)

Bounds on Kolmogorov widths and sampling recovery for classes with small mixed smoothness. - Vladimir N. Temlyakov; Tino Ullrich (J. Complex., 2021)

On universal sampling representation. - Vladimir N. Temlyakov (CoRR, 2022)

Some improved bounds in sampling discretization of integral norms. - Feng Dai; Egor D. Kosov; Vladimir N. Temlyakov (CoRR, 2022)

Approximation of functions with small mixed smoothness in the uniform norm. - Vladimir N. Temlyakov; Tino Ullrich (J. Approx. Theory, 2022)

Sampling discretization and related problems. - Boris S. Kashin; Egor D. Kosov; Irina V. Limonova; Vladimir N. Temlyakov (J. Complex., 2022)

Universal discretization and sparse sampling recovery. - Feng Dai; Vladimir N. Temlyakov (CoRR, 2023)

Random points are good for universal discretization. - Feng Dai; Vladimir N. Temlyakov (CoRR, 2023)

On the rate of convergence of greedy algorithms. - Vladimir N. Temlyakov (CoRR, 2023)

Rate of convergence of Thresholding Greedy Algorithms. - Vladimir N. Temlyakov (CoRR, 2023)

Sampling discretization of the uniform norm and applications. - Egor D. Kosov; Vladimir N. Temlyakov (CoRR, 2023)

On universal sampling recovery in the uniform norm. - Vladimir N. Temlyakov (CoRR, 2023)

Lebesgue-type inequalities in sparse sampling recovery. - Feng Dai; Vladimir N. Temlyakov (CoRR, 2023)

On the cardinality of lower sets and universal discretization. - Feng Dai; A. V. Prymak; A. Shadrin; Vladimir N. Temlyakov; Sergey Tikhonov (J. Complex., 2023)

Sampling discretization error of integral norms for function classes with small smoothness. - Vladimir N. Temlyakov (J. Approx. Theory, 2023)

One-sided discretization inequalities and sampling recovery. - Irina V. Limonova; Yuri Malykhin; Vladimir N. Temlyakov (CoRR, 2024)

Twenty-five years of greedy bases. - Fernando Albiac; José L. Ansorena; Vladimir N. Temlyakov (J. Approx. Theory, 2025)

Universal discretization and sparse recovery. - F. Dai; Vladimir N. Temlyakov (J. Approx. Theory, 2025)

Bounds for the sampling discretization error and their applications to the universal sampling discretization. - Egor D. Kosov; Vladimir N. Temlyakov (J. Complex., 2025)