Vladimir N. Temlyakov
Applied Mathematics · 1992–2018
A researcher in the Science corpus: 9 papers; trusts 49 researchers and is trusted by 81 researchers here, as inferred from the citation graph.
Subfields
- Applied Mathematics — 30 citations into it
- Computational Mechanics — 26 citations into it; #513 of 10,001 by trust here, #525 by citations
- Numerical Analysis — 20 citations into it
- Statistics and Probability — 18 citations into it
- Computational Theory and Mathematics — 12 citations into it
- Mathematical Physics — 12 citations into it; #1,728 of 8,562 by trust here, #3,482 by citations
- Computer Vision and Pattern Recognition — 10 citations into it; #3,584 of 21,575 by trust here, #3,765 by citations
- Signal Processing — 9 citations into it; #445 of 7,572 by trust here, #530 by citations
Whom Vladimir N. Temlyakov trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Joel A. Tropp
- E.J. Candes
- Andrew R. Barron
- Przemyslaw Wojtaszczyk
- Albert Cohen
- Rémi Gribonval
- Stéphane Mallat
- David L. Donoho
- Jerome H. Friedman
- Deanna Needell
Who trusts Vladimir N. Temlyakov overall
- É. Cancès
- D. Dung
- Antonio Falcó
- Virginie Ehrlacher
- Tony Lelièvre
- Anthony Nouy
- David L. Donoho
- Tong Zhang
- Gustavo Garrigós
- André Uschmajew
Papers from Vladimir N. Temlyakov's perspective
Ordered by how strongly the researchers Vladimir N. Temlyakov trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- Stable signal recovery from incomplete and inaccurate measurements
- Decoding by linear programming
- The Elements of Statistical Learning
- Uncertainty principles and ideal atomic decomposition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- ImageNet classification with deep convolutional neural networks
- Greed is good: algorithmic results for sparse approximation (IEEE Transactions on Information Theory)
- Matching pursuits with time-frequency dictionaries
Their papers
- Stable recovery of sparse overcomplete representations in the presence of noise (2006) — 2,309 citations
- Multivariate Approximation (2018) — 74 citations
- The Marcinkiewicz-Type Discretization Theorems (2017) — 63 citations
- Hyperbolic Cross Approximation (2016) — 305 citations
- Greedy approximation (2008) — 422 citations
- Mathematical Methods for Supervised Learning (2005)
- The Thresholding Greedy Algorithm, Greedy Bases, and Duality (2003) — 177 citations
- Greedy Approximation with Regard to Bases and General Minimal Systems (2002) — 54 citations
- Estimates of best bilinear approximations of functions and approximation numbers of integral operators (1992)