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Marc Teboulle
Person information
- affiliation: Tel Aviv University, School of Mathematical Sciences, Israel
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2020 – today
- 2024
- [j75]Eyal Cohen, D. Russell Luke, Titus Pinta
, Shoham Sabach, Marc Teboulle:
A semi-Bregman proximal alternating method for a class of nonconvex problems: local and global convergence analysis. J. Glob. Optim. 89(1): 33-55 (2024) - 2023
- [j74]Marc Teboulle
An elementary approach to tight worst case complexity analysis of gradient based methods. Math. Program. 201(1): 63-96 (2023) - 2022
- [j73]Eyal Cohen, Nadav Hallak
A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints. J. Optim. Theory Appl. 193(1): 324-353 (2022) - [j72]Shoham Sabach, Marc Teboulle
Faster Lagrangian-Based Methods in Convex Optimization. SIAM J. Optim. 32(1): 204-227 (2022) - 2021
- [j71]Amir Beck, Marc Teboulle
Dual Randomized Coordinate Descent Method for Solving a Class of Nonconvex Problems. SIAM J. Optim. 31(3): 1877-1896 (2021) - 2020
- [j70]Nadav Hallak
Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach. J. Optim. Theory Appl. 186(2): 480-503 (2020) - [j69]D. Russell Luke
Necessary conditions for linear convergence of iterated expansive, set-valued mappings. Math. Program. 180(1): 1-31 (2020) - [j68]Marc Teboulle
Novel Proximal Gradient Methods for Nonnegative Matrix Factorization with Sparsity Constraints. SIAM J. Imaging Sci. 13(1): 381-421 (2020) - [i3]Shoham Sabach, Marc Teboulle:
Faster Lagrangian-Based Methods in Convex Optimization. CoRR abs/2010.14314 (2020)
2010 – 2019
- 2019
- [j67]Heinz H. Bauschke
On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity. J. Optim. Theory Appl. 182(3): 1068-1087 (2019) - [j66]Nadav Hallak
A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization. Oper. Res. Lett. 47(5): 421-426 (2019) - [j65]D. Russell Luke, Shoham Sabach, Marc Teboulle
Optimization on Spheres: Models and Proximal Algorithms with Computational Performance Comparisons. SIAM J. Math. Data Sci. 1(3): 408-445 (2019) - 2018
- [j64]Jérôme Bolte, Shoham Sabach, Marc Teboulle
Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence. Math. Oper. Res. 43(4): 1210-1232 (2018) - [j63]Marc Teboulle
A simplified view of first order methods for optimization. Math. Program. 170(1): 67-96 (2018) - [j62]Jérôme Bolte, Shoham Sabach, Marc Teboulle
First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. SIAM J. Optim. 28(3): 2131-2151 (2018) - 2017
- [j61]D. Russell Luke, Shoham Sabach, Marc Teboulle, Kobi Zatlawey:
A simple globally convergent algorithm for the nonsmooth nonconvex single source localization problem. J. Glob. Optim. 69(4): 889-909 (2017) - [j60]Heinz H. Bauschke
A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications. Math. Oper. Res. 42(2): 330-348 (2017) - [i2]Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd:
First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. CoRR abs/1706.06461 (2017) - 2016
- [j59]Ron Shefi, Marc Teboulle:
On the rate of convergence of the proximal alternating linearized minimization algorithm for convex problems. EURO J. Comput. Optim. 4(1): 27-46 (2016) - [j58]Ron Shefi, Marc Teboulle:
A dual method for minimizing a nonsmooth objective over one smooth inequality constraint. Math. Program. 159(1-2): 137-164 (2016) - [j57]Yoel Drori, Marc Teboulle:
An optimal variant of Kelley's cutting-plane method. Math. Program. 160(1-2): 321-351 (2016) - [j56]Amir Beck, Shoham Sabach, Marc Teboulle:
An Alternating Semiproximal Method for Nonconvex Regularized Structured Total Least Squares Problems. SIAM J. Matrix Anal. Appl. 37(3): 1129-1150 (2016) - 2015
- [j55]Yoel Drori, Shoham Sabach, Marc Teboulle:
A simple algorithm for a class of nonsmooth convex-concave saddle-point problems. Oper. Res. Lett. 43(2): 209-214 (2015) - 2014
- [j54]Yoel Drori, Marc Teboulle:
Performance of first-order methods for smooth convex minimization: a novel approach. Math. Program. 145(1-2): 451-482 (2014) - [j53]Jérôme Bolte, Shoham Sabach, Marc Teboulle:
Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Math. Program. 146(1-2): 459-494 (2014) - [j52]Amir Beck, Marc Teboulle:
A fast dual proximal gradient algorithm for convex minimization and applications. Oper. Res. Lett. 42(1): 1-6 (2014) - [j51]Ron Shefi, Marc Teboulle:
Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization. SIAM J. Optim. 24(1): 269-297 (2014) - [j50]Amir Beck, Angelia Nedic
An O(1/k) Gradient Method for Network Resource Allocation Problems. IEEE Trans. Control. Netw. Syst. 1(1): 64-73 (2014) - 2013
- [j49]Ronny Luss, Marc Teboulle:
Conditional Gradient Algorithmsfor Rank-One Matrix Approximations with a Sparsity Constraint. SIAM Rev. 55(1): 65-98 (2013) - 2012
- [j48]Amir Beck, Yoel Drori, Marc Teboulle:
A new semidefinite programming relaxation scheme for a class of quadratic matrix problems. Oper. Res. Lett. 40(4): 298-302 (2012) - [j47]Amir Beck, Marc Teboulle:
Smoothing and First Order Methods: A Unified Framework. SIAM J. Optim. 22(2): 557-580 (2012) - 2011
- [j46]Ronny Luss, Marc Teboulle:
Convex approximations to sparse PCA via Lagrangian duality. Oper. Res. Lett. 39(1): 57-61 (2011) - [p3]Amir Beck, Marc Teboulle:
A Linearly Convergent Algorithm for Solving a Class of Nonconvex/Affine Feasibility Problems. Fixed-Point Algorithms for Inverse Problems in Science and Engineering 2011: 33-48 - [i1]Ronny Luss, Marc Teboulle:
Conditional Gradient Algorithms for Rank-One Matrix Approximations with a Sparsity Constraint. CoRR abs/1107.1163 (2011) - 2010
- [j45]Alfred Auslender, Ron Shefi, Marc Teboulle:
A Moving Balls Approximation Method for a Class of Smooth Constrained Minimization Problems. SIAM J. Optim. 20(6): 3232-3259 (2010) - [p2]Amir Beck, Marc Teboulle:
Gradient-based algorithms with applications to signal-recovery problems. Convex Optimization in Signal Processing and Communications 2010: 42-88
2000 – 2009
- 2009
- [j44]Hédy Attouch, Roberto Cominetti
Foreword: Special issue on nonlinear convex optimization and variational inequalities. Math. Program. 116(1-2): 1-3 (2009) - [j43]Amir Beck, Marc Teboulle:
A convex optimization approach for minimizing the ratio of indefinite quadratic functions over an ellipsoid. Math. Program. 118(1): 13-35 (2009) - [j42]Alfred Auslender, Marc Teboulle:
Projected subgradient methods with non-Euclidean distances for non-differentiable convex minimization and variational inequalities. Math. Program. 120(1): 27-48 (2009) - [j41]Amir Beck, Marc Teboulle:
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. SIAM J. Imaging Sci. 2(1): 183-202 (2009) - [j40]Amir Beck, Marc Teboulle:
Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems. IEEE Trans. Image Process. 18(11): 2419-2434 (2009) - [c1]Amir Beck, Marc Teboulle:
A fast Iterative Shrinkage-Thresholding Algorithm with application to wavelet-based image deblurring. ICASSP 2009: 693-696 - [r1]Marc Teboulle:
Lagrangian Multipliers Methods for Convex Programming. Encyclopedia of Optimization 2009: 1813-1818 - 2008
- [j39]Amir Beck, Marc Teboulle, Zahar Chikishev:
Iterative Minimization Schemes for Solving the Single Source Localization Problem. SIAM J. Optim. 19(3): 1397-1416 (2008) - [j38]Yonina C. Eldar, Amir Beck, Marc Teboulle:
A Minimax Chebyshev Estimator for Bounded Error Estimation. IEEE Trans. Signal Process. 56(4): 1388-1397 (2008) - 2007
- [j37]Alfred Auslender, Paulo J. S. Silva
Nonmonotone projected gradient methods based on barrier and Euclidean distances. Comput. Optim. Appl. 38(3): 305-327 (2007) - [j36]Marc Teboulle:
A Unified Continuous Optimization Framework for Center-Based Clustering Methods. J. Mach. Learn. Res. 8: 65-102 (2007) - 2006
- [j35]Amir Beck, Marc Teboulle:
A Linearly Convergent Dual-Based Gradient Projection Algorithm for Quadratically Constrained Convex Minimization. Math. Oper. Res. 31(2): 398-417 (2006) - [j34]Mustafa Ç. Pinar, Marc Teboulle:
On semidefinite bounds for maximization of a non-convex quadratic objective over the l1 unit ball. RAIRO Oper. Res. 40(3): 253-265 (2006) - [j33]Alfred Auslender, Marc Teboulle:
Interior Gradient and Proximal Methods for Convex and Conic Optimization. SIAM J. Optim. 16(3): 697-725 (2006) - [j32]Amir Beck, Aharon Ben-Tal, Marc Teboulle:
Finding a Global Optimal Solution for a Quadratically Constrained Fractional Quadratic Problem with Applications to the Regularized Total Least Squares. SIAM J. Matrix Anal. Appl. 28(2): 425-445 (2006) - [p1]Marc Teboulle, Pavel Berkhin, Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan:
Clustering with Entropy-Like k-Means Algorithms. Grouping Multidimensional Data 2006: 127-160 - [e1]Jacob Kogan, Charles K. Nicholas, Marc Teboulle:
Grouping Multidimensional Data - Recent Advances in Clustering. Springer 2006, ISBN 978-3-540-28348-5 [contents] - 2005
- [j31]Jacob Kogan, Marc Teboulle, Charles K. Nicholas:
Data Driven Similarity Measures for k-Means Like Clustering Algorithms. Inf. Retr. 8(2): 331-349 (2005) - [j30]Alfred Auslender, Marc Teboulle:
Interior projection-like methods for monotone variational inequalities. Math. Program. 104(1): 39-68 (2005) - 2004
- [j29]Amir Beck, Marc Teboulle:
A conditional gradient method with linear rate of convergence for solving convex linear systems. Math. Methods Oper. Res. 59(2): 235-247 (2004) - [j28]Alfred Auslender, Marc Teboulle:
Interior Gradient and Epsilon-Subgradient Descent Methods for Constrained Convex Minimization. Math. Oper. Res. 29(1): 1-26 (2004) - 2003
- [j27]Amir Beck, Marc Teboulle:
Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems. Optim. Methods Softw. 18(4): 377-394 (2003) - [j26]Amir Beck, Marc Teboulle:
Mirror descent and nonlinear projected subgradient methods for convex optimization. Oper. Res. Lett. 31(3): 167-175 (2003) - [j25]Jérôme Bolte, Marc Teboulle:
Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems. SIAM J. Control. Optim. 42(4): 1266-1292 (2003) - 2001
- [j24]Alfred Auslender, Marc Teboulle:
Entropic proximal decomposition methods for convex programs and variational inequalities. Math. Program. 91(1): 33-47 (2001) - 2000
- [j23]Amir Beck, Marc Teboulle:
A probabilistic result for the max-cut problem on random graphs. Oper. Res. Lett. 27(5): 209-214 (2000) - [j22]Alfred Auslender, Marc Teboulle:
Lagrangian Duality and Related Multiplier Methods for Variational Inequality Problems. SIAM J. Optim. 10(4): 1097-1115 (2000) - [j21]Amir Beck, Marc Teboulle:
Global Optimality Conditions for Quadratic Optimization Problems with Binary Constraints. SIAM J. Optim. 11(1): 179-188 (2000)
1990 – 1999
- 1999
- [j20]Alfred Auslender, Marc Teboulle, Sami Ben-Tiba:
A Logarithmic-Quadratic Proximal Method for Variational Inequalities. Comput. Optim. Appl. 12(1-3): 31-40 (1999) - [j19]Alfred Auslender, Marc Teboulle, Sami Ben-Tiba:
Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels. Math. Oper. Res. 24(3): 645-668 (1999) - 1998
- [j18]Moshe Hershkovitz, Marc Teboulle:
Sensitivity analysis for a class of robotic grasping quality functionals. Robotica 16(2): 227-235 (1998) - [j17]Moshe Doljansky, Marc Teboulle:
An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming. SIAM J. Optim. 9(1): 1-13 (1998) - 1997
- [j16]Moshe Hershkovitz, Uri Tasch, Marc Teboulle, Joseph Tzelgov:
Experimental validation of an optimization formulation of the human grasping quality sense. J. Field Robotics 14(11): 753-766 (1997) - [j15]Marc Teboulle:
Convergence of Proximal-Like Algorithms. SIAM J. Optim. 7(4): 1069-1083 (1997) - 1996
- [j14]Aharon Ben-Tal, Marc Teboulle:
Hidden convexity in some nonconvex quadratically constrained quadratic programming. Math. Program. 72: 51-63 (1996) - [j13]Roman A. Polyak, Marc Teboulle:
Nonlinear rescaling and proximal-like methods in convex optimization. Math. Program. 76: 265-284 (1996) - [j12]Aharon Ben-Tal, Marc Teboulle:
A Conjugate Duality Scheme Generating a New Class of Differentiable Duals. SIAM J. Optim. 6(3): 617-625 (1996) - 1995
- [j11]Moshe Hershkovitz, Uri Tasch, Marc Teboulle:
Toeard a formulation of the human grasping quality sense. J. Field Robotics 12(4): 249-256 (1995) - [j10]Alfredo N. Iusem, Marc Teboulle:
Convergence Rate Analysis of Nonquadratic Proximal Methods for Convex and Linear Programming. Math. Oper. Res. 20(3): 657-677 (1995) - 1994
- [j9]Alfredo N. Iusem, Benar Fux Svaiter
Entropy-Like Proximal Methods in Convex Programming. Math. Oper. Res. 19(4): 790-814 (1994) - [j8]Gong Chen, Marc Teboulle:
A proximal-based decomposition method for convex minimization problems. Math. Program. 64: 81-101 (1994) - 1993
- [j7]Gong Chen, Marc Teboulle:
Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions. SIAM J. Optim. 3(3): 538-543 (1993) - [j6]Marc Teboulle, Igor Vajda:
Convergence of best phi-entropy estimates. IEEE Trans. Inf. Theory 39(1): 297-301 (1993) - 1992
- [j5]Marc Teboulle:
Entropic Proximal Mappings with Applications to Nonlinear Programming. Math. Oper. Res. 17(3): 670-690 (1992) - 1991
- [j4]Aharon Ben-Tal, Marc Teboulle:
Portfolio theory for the recourse certainty equivalent maximizing investor. Ann. Oper. Res. 31(1): 479-499 (1991)
1980 – 1989
- 1989
- [j3]John R. Birge
Upper Bounds on the Expected Value of a Convex Function Using Gradient and Conjugate Function Information. Math. Oper. Res. 14(4): 745-759 (1989) - 1987
- [j2]Aharon Ben-Tal, Marc Teboulle:
Penalty Functions and Duality in Stochastic Programming Via ϕ-Divergence Functionals. Math. Oper. Res. 12(2): 224-240 (1987) - 1986
- [j1]Aharon Ben-Tal, Marc Teboulle:
Rate distortion theory with generalized information measures via convex programming duality. IEEE Trans. Inf. Theory 32(5): 630-641 (1986)
Coauthor Index
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