Követés
Marc Teboulle
Marc Teboulle
Professor, School of Mathematical Sciences, Tel Aviv University
E-mail megerősítve itt: tauex.tau.ac.il - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A Beck, M Teboulle
SIAM journal on imaging sciences 2 (1), 183-202, 2009
141502009
Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems
A Beck, M Teboulle
IEEE transactions on image processing 18 (11), 2419-2434, 2009
24232009
Proximal alternating linearized minimization for nonconvex and nonsmooth problems
J Bolte, S Sabach, M Teboulle
Mathematical Programming 146 (1), 459-494, 2014
18322014
Mirror descent and nonlinear projected subgradient methods for convex optimization
A Beck, M Teboulle
Operations Research Letters 31 (3), 167-175, 2003
14862003
Convergence analysis of a proximal-like minimization algorithm using Bregman functions
G Chen, M Teboulle
SIAM Journal on Optimization 3 (3), 538-543, 1993
6541993
Asymptotic cones and functions in optimization and variational inequalities
A Auslender, M Teboulle
Springer Science & Business Media, 2006
5662006
Gradient-based algorithms with applications to signal-recovery problems.
A Beck, M Teboulle
Convex optimization in signal processing and communications, 42-88, 2010
4972010
A proximal-based decomposition method for convex minimization problems
G Chen, M Teboulle
Mathematical Programming 64 (1), 81-101, 1994
4961994
An old‐new concept of convex risk measures: The optimized certainty equivalent
A Ben‐Tal, M Teboulle
Mathematical Finance 17 (3), 449-476, 2007
4872007
A descent lemma beyond Lipschitz gradient continuity: first-order methods revisited and applications
HH Bauschke, J Bolte, M Teboulle
Mathematics of Operations Research 42 (2), 330-348, 2017
4802017
Interior gradient and proximal methods for convex and conic optimization
A Auslender, M Teboulle
SIAM Journal on Optimization 16 (3), 697-725, 2006
3772006
Entropic proximal mappings with applications to nonlinear programming
M Teboulle
Mathematics of Operations Research 17 (3), 670-690, 1992
3471992
Smoothing and first order methods: A unified framework
A Beck, M Teboulle
SIAM Journal on Optimization 22 (2), 557-580, 2012
3352012
Performance of first-order methods for smooth convex minimization: a novel approach
Y Drori, M Teboulle
Mathematical Programming 145 (1), 451-482, 2014
3212014
A fast iterative shrinkage-thresholding algorithm with application to wavelet-based image deblurring
A Beck, M Teboulle
2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009
2952009
Expected utility, penalty functions, and duality in stochastic nonlinear programming
A Ben-Tal, M Teboulle
Management Science 32 (11), 1445-1466, 1986
2491986
A logarithmic-quadratic proximal method for variational inequalities
A Auslender, M Teboulle, S Ben-Tiba
Computational Optimization: A Tribute to Olvi Mangasarian Volume I, 31-40, 1999
2411999
First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems
J Bolte, S Sabach, M Teboulle, Y Vaisbourd
SIAM Journal on Optimization 28 (3), 2131-2151, 2018
2302018
Entropy-like proximal methods in convex programming
AN Iusem, BF Svaiter, M Teboulle
Mathematics of Operations Research 19 (4), 790-814, 1994
2301994
An Gradient Method for Network Resource Allocation Problems
A Beck, A Nedić, A Ozdaglar, M Teboulle
IEEE Transactions on Control of Network Systems 1 (1), 64-73, 2014
2262014
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