Rate distortion theory with generalized information measures via convex programming duality. - Aharon Ben-Tal; Marc Teboulle (IEEE Trans. Inf. Theory, 1986)

Penalty Functions and Duality in Stochastic Programming Via ϕ-Divergence Functionals. - Aharon Ben-Tal; Marc Teboulle (Math. Oper. Res., 1987)

Upper Bounds on the Expected Value of a Convex Function Using Gradient and Conjugate Function Information. - John R. Birge; Marc Teboulle (Math. Oper. Res., 1989)

Portfolio theory for the recourse certainty equivalent maximizing investor. - Aharon Ben-Tal; Marc Teboulle (Ann. Oper. Res., 1991)

Entropic Proximal Mappings with Applications to Nonlinear Programming. - Marc Teboulle (Math. Oper. Res., 1992)

Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions. - Gong Chen; Marc Teboulle (SIAM J. Optim., 1993)

Convergence of best phi-entropy estimates. - Marc Teboulle; Igor Vajda (IEEE Trans. Inf. Theory, 1993)

Entropy-Like Proximal Methods in Convex Programming. - Alfredo N. Iusem; Benar Fux Svaiter; Marc Teboulle (Math. Oper. Res., 1994)

A proximal-based decomposition method for convex minimization problems. - Gong Chen; Marc Teboulle (Math. Program., 1994)

Toeard a formulation of the human grasping quality sense. - Moshe Hershkovitz; Uri Tasch; Marc Teboulle (J. Field Robotics, 1995)

Convergence Rate Analysis of Nonquadratic Proximal Methods for Convex and Linear Programming. - Alfredo N. Iusem; Marc Teboulle (Math. Oper. Res., 1995)

Hidden convexity in some nonconvex quadratically constrained quadratic programming. - Aharon Ben-Tal; Marc Teboulle (Math. Program., 1996)

Nonlinear rescaling and proximal-like methods in convex optimization. - Roman A. Polyak; Marc Teboulle (Math. Program., 1996)

A Conjugate Duality Scheme Generating a New Class of Differentiable Duals. - Aharon Ben-Tal; Marc Teboulle (SIAM J. Optim., 1996)

Experimental validation of an optimization formulation of the human grasping quality sense. - Moshe Hershkovitz; Uri Tasch; Marc Teboulle; Joseph Tzelgov (J. Field Robotics, 1997)

Convergence of Proximal-Like Algorithms. - Marc Teboulle (SIAM J. Optim., 1997)

Sensitivity analysis for a class of robotic grasping quality functionals. - Moshe Hershkovitz; Marc Teboulle (Robotica, 1998)

An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming. - Moshe Doljansky; Marc Teboulle (SIAM J. Optim., 1998)

A Logarithmic-Quadratic Proximal Method for Variational Inequalities. - Alfred Auslender; Marc Teboulle; Sami Ben-Tiba (Comput. Optim. Appl., 1999)

Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels. - Alfred Auslender; Marc Teboulle; Sami Ben-Tiba (Math. Oper. Res., 1999)

A probabilistic result for the max-cut problem on random graphs. - Amir Beck; Marc Teboulle (Oper. Res. Lett., 2000)

Lagrangian Duality and Related Multiplier Methods for Variational Inequality Problems. - Alfred Auslender; Marc Teboulle (SIAM J. Optim., 2000)

Global Optimality Conditions for Quadratic Optimization Problems with Binary Constraints. - Amir Beck; Marc Teboulle (SIAM J. Optim., 2000)

Entropic proximal decomposition methods for convex programs and variational inequalities. - Alfred Auslender; Marc Teboulle (Math. Program., 2001)

Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems. - Amir Beck; Marc Teboulle (Optim. Methods Softw., 2003)

Mirror descent and nonlinear projected subgradient methods for convex optimization. - Amir Beck; Marc Teboulle (Oper. Res. Lett., 2003)

Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems. - Jérôme Bolte; Marc Teboulle (SIAM J. Control. Optim., 2003)

A conditional gradient method with linear rate of convergence for solving convex linear systems. - Amir Beck; Marc Teboulle (Math. Methods Oper. Res., 2004)

Interior Gradient and Epsilon-Subgradient Descent Methods for Constrained Convex Minimization. - Alfred Auslender; Marc Teboulle (Math. Oper. Res., 2004)

Data Driven Similarity Measures for k-Means Like Clustering Algorithms. - Jacob Kogan; Marc Teboulle; Charles K. Nicholas (Inf. Retr., 2005)

Interior projection-like methods for monotone variational inequalities. - Alfred Auslender; Marc Teboulle (Math. Program., 2005)

Clustering with Entropy-Like k-Means Algorithms. - Marc Teboulle; Pavel Berkhin; Inderjit S. Dhillon; Yuqiang Guan; Jacob Kogan (Grouping Multidimensional Data, 2006)

A Linearly Convergent Dual-Based Gradient Projection Algorithm for Quadratically Constrained Convex Minimization. - Amir Beck; Marc Teboulle (Math. Oper. Res., 2006)

On semidefinite bounds for maximization of a non-convex quadratic objective over the l1 unit ball. - Mustafa Ç. Pinar; Marc Teboulle (RAIRO Oper. Res., 2006)

Interior Gradient and Proximal Methods for Convex and Conic Optimization. - Alfred Auslender; Marc Teboulle (SIAM J. Optim., 2006)

Finding a Global Optimal Solution for a Quadratically Constrained Fractional Quadratic Problem with Applications to the Regularized Total Least Squares. - Amir Beck; Aharon Ben-Tal; Marc Teboulle (SIAM J. Matrix Anal. Appl., 2006)

Nonmonotone projected gradient methods based on barrier and Euclidean distances. - Alfred Auslender; Paulo J. S. Silva; Marc Teboulle (Comput. Optim. Appl., 2007)

A Unified Continuous Optimization Framework for Center-Based Clustering Methods. - Marc Teboulle (J. Mach. Learn. Res., 2007)

Iterative Minimization Schemes for Solving the Single Source Localization Problem. - Amir Beck; Marc Teboulle; Zahar Chikishev (SIAM J. Optim., 2008)

A Minimax Chebyshev Estimator for Bounded Error Estimation. - Yonina C. Eldar; Amir Beck; Marc Teboulle (IEEE Trans. Signal Process., 2008)

A fast Iterative Shrinkage-Thresholding Algorithm with application to wavelet-based image deblurring. - Amir Beck; Marc Teboulle (ICASSP, 2009)

Foreword: Special issue on nonlinear convex optimization and variational inequalities. - Hédy Attouch; Roberto Cominetti; Marc Teboulle (Math. Program., 2009)

Projected subgradient methods with non-Euclidean distances for non-differentiable convex minimization and variational inequalities. - Alfred Auslender; Marc Teboulle (Math. Program., 2009)

A convex optimization approach for minimizing the ratio of indefinite quadratic functions over an ellipsoid. - Amir Beck; Marc Teboulle (Math. Program., 2009)

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. - Amir Beck; Marc Teboulle (SIAM J. Imaging Sci., 2009)

Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems. - Amir Beck; Marc Teboulle (IEEE Trans. Image Process., 2009)

Lagrangian Multipliers Methods for Convex Programming. - Marc Teboulle (Encyclopedia of Optimization, 2009)

Gradient-based algorithms with applications to signal-recovery problems. - Amir Beck; Marc Teboulle (Convex Optimization in Signal Processing and Communications, 2010)

A Moving Balls Approximation Method for a Class of Smooth Constrained Minimization Problems. - Alfred Auslender; Ron Shefi; Marc Teboulle (SIAM J. Optim., 2010)

A Linearly Convergent Algorithm for Solving a Class of Nonconvex/Affine Feasibility Problems. - Amir Beck; Marc Teboulle (Fixed-Point Algorithms for Inverse Problems in Science and Engineering, 2011)

Conditional Gradient Algorithms for Rank-One Matrix Approximations with a Sparsity Constraint - Ronny Luss; Marc Teboulle (CoRR, 2011)

Convex approximations to sparse PCA via Lagrangian duality. - Ronny Luss; Marc Teboulle (Oper. Res. Lett., 2011)

A new semidefinite programming relaxation scheme for a class of quadratic matrix problems. - Amir Beck; Yoel Drori; Marc Teboulle (Oper. Res. Lett., 2012)

Smoothing and First Order Methods: A Unified Framework. - Amir Beck; Marc Teboulle (SIAM J. Optim., 2012)

Conditional Gradient Algorithmsfor Rank-One Matrix Approximations with a Sparsity Constraint. - Ronny Luss; Marc Teboulle (SIAM Rev., 2013)

Proximal alternating linearized minimization for nonconvex and nonsmooth problems. - Jérôme Bolte; Shoham Sabach; Marc Teboulle (Math. Program., 2014)

Performance of first-order methods for smooth convex minimization: a novel approach. - Yoel Drori; Marc Teboulle (Math. Program., 2014)

A fast dual proximal gradient algorithm for convex minimization and applications. - Amir Beck; Marc Teboulle (Oper. Res. Lett., 2014)

Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization. - Ron Shefi; Marc Teboulle (SIAM J. Optim., 2014)

An O(1/k) Gradient Method for Network Resource Allocation Problems. - Amir Beck; Angelia Nedic; Asuman E. Ozdaglar; Marc Teboulle (IEEE Trans. Control. Netw. Syst., 2014)

A simple algorithm for a class of nonsmooth convex-concave saddle-point problems. - Yoel Drori; Shoham Sabach; Marc Teboulle (Oper. Res. Lett., 2015)

On the rate of convergence of the proximal alternating linearized minimization algorithm for convex problems. - Ron Shefi; Marc Teboulle (EURO J. Comput. Optim., 2016)

An optimal variant of Kelley's cutting-plane method. - Yoel Drori; Marc Teboulle (Math. Program., 2016)

A dual method for minimizing a nonsmooth objective over one smooth inequality constraint. - Ron Shefi; Marc Teboulle (Math. Program., 2016)

An Alternating Semiproximal Method for Nonconvex Regularized Structured Total Least Squares Problems. - Amir Beck; Shoham Sabach; Marc Teboulle (SIAM J. Matrix Anal. Appl., 2016)

A simple globally convergent algorithm for the nonsmooth nonconvex single source localization problem. - D. Russell Luke; Shoham Sabach; Marc Teboulle; Kobi Zatlawey (J. Glob. Optim., 2017)

A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications. - Heinz H. Bauschke; Jérôme Bolte; Marc Teboulle (Math. Oper. Res., 2017)

Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence. - Jérôme Bolte; Shoham Sabach; Marc Teboulle (Math. Oper. Res., 2018)

A simplified view of first order methods for optimization. - Marc Teboulle (Math. Program., 2018)

First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. - Jérôme Bolte; Shoham Sabach; Marc Teboulle; Yakov Vaisbourd (SIAM J. Optim., 2018)

On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity. - Heinz H. Bauschke; Jérôme Bolte; Jiawei Chen; Marc Teboulle; Xianfu Wang (J. Optim. Theory Appl., 2019)

A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization. - Nadav Hallak; Marc Teboulle (Oper. Res. Lett., 2019)

Optimization on Spheres: Models and Proximal Algorithms with Computational Performance Comparisons. - D. Russell Luke; Shoham Sabach; Marc Teboulle (SIAM J. Math. Data Sci., 2019)

Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach. - Nadav Hallak; Marc Teboulle (J. Optim. Theory Appl., 2020)

Necessary conditions for linear convergence of iterated expansive, set-valued mappings. - D. Russell Luke; Marc Teboulle; Nguyen H. Thao (Math. Program., 2020)

Novel Proximal Gradient Methods for Nonnegative Matrix Factorization with Sparsity Constraints. - Marc Teboulle; Yakov Vaisbourd (SIAM J. Imaging Sci., 2020)

Dual Randomized Coordinate Descent Method for Solving a Class of Nonconvex Problems. - Amir Beck; Marc Teboulle (SIAM J. Optim., 2021)

A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints. - Eyal Cohen; Nadav Hallak; Marc Teboulle (J. Optim. Theory Appl., 2022)

Faster Lagrangian-Based Methods in Convex Optimization. - Shoham Sabach; Marc Teboulle (SIAM J. Optim., 2022)

An Adaptive Lagrangian-Based Scheme for Nonconvex Composite Optimization. - Nadav Hallak; Marc Teboulle (Math. Oper. Res., 2023)

An elementary approach to tight worst case complexity analysis of gradient based methods. - Marc Teboulle; Yakov Vaisbourd (Math. Program., 2023)

A semi-Bregman proximal alternating method for a class of nonconvex problems: local and global convergence analysis. - Eyal Cohen; D. Russell Luke; Titus Pinta; Shoham Sabach; Marc Teboulle (J. Glob. Optim., 2024)

Exact Lipschitz Regularization of Convex Optimization Problems. - Amir Beck; Marc Teboulle (J. Optim. Theory Appl., 2024)

Alternating and Parallel Proximal Gradient Methods for Nonsmooth, Nonconvex Minimax: A Unified Convergence Analysis. - Eyal Cohen; Marc Teboulle (Math. Oper. Res., 2025)