Marc Teboulle

  • Tel Aviv University, School of Mathematical Sciences, Israel

According to our database1, Marc Teboulle authored at least 78 papers between 1986 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:



Dual Randomized Coordinate Descent Method for Solving a Class of Nonconvex Problems.
SIAM J. Optim., 2021

Novel Proximal Gradient Methods for Nonnegative Matrix Factorization with Sparsity Constraints.
SIAM J. Imaging Sci., 2020

Necessary conditions for linear convergence of iterated expansive, set-valued mappings.
Math. Program., 2020

Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach.
J. Optim. Theory Appl., 2020

Faster Lagrangian-Based Methods in Convex Optimization.
CoRR, 2020

Optimization on Spheres: Models and Proximal Algorithms with Computational Performance Comparisons.
SIAM J. Math. Data Sci., 2019

A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization.
Oper. Res. Lett., 2019

On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity.
J. Optim. Theory Appl., 2019

First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems.
SIAM J. Optim., 2018

A simplified view of first order methods for optimization.
Math. Program., 2018

Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence.
Math. Oper. Res., 2018

A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications.
Math. Oper. Res., 2017

A simple globally convergent algorithm for the nonsmooth nonconvex single source localization problem.
J. Glob. Optim., 2017

An Alternating Semiproximal Method for Nonconvex Regularized Structured Total Least Squares Problems.
SIAM J. Matrix Anal. Appl., 2016

A dual method for minimizing a nonsmooth objective over one smooth inequality constraint.
Math. Program., 2016

An optimal variant of Kelley's cutting-plane method.
Math. Program., 2016

On the rate of convergence of the proximal alternating linearized minimization algorithm for convex problems.
EURO J. Comput. Optim., 2016

A simple algorithm for a class of nonsmooth convex-concave saddle-point problems.
Oper. Res. Lett., 2015

An O(1/k) Gradient Method for Network Resource Allocation Problems.
IEEE Trans. Control. Netw. Syst., 2014

Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization.
SIAM J. Optim., 2014

A fast dual proximal gradient algorithm for convex minimization and applications.
Oper. Res. Lett., 2014

Performance of first-order methods for smooth convex minimization: a novel approach.
Math. Program., 2014

Proximal alternating linearized minimization for nonconvex and nonsmooth problems.
Math. Program., 2014

Conditional Gradient Algorithmsfor Rank-One Matrix Approximations with a Sparsity Constraint.
SIAM Rev., 2013

Smoothing and First Order Methods: A Unified Framework.
SIAM J. Optim., 2012

A new semidefinite programming relaxation scheme for a class of quadratic matrix problems.
Oper. Res. Lett., 2012

Convex approximations to sparse PCA via Lagrangian duality.
Oper. Res. Lett., 2011

Conditional Gradient Algorithms for Rank-One Matrix Approximations with a Sparsity Constraint
CoRR, 2011

A Linearly Convergent Algorithm for Solving a Class of Nonconvex/Affine Feasibility Problems.
Proceedings of the Fixed-Point Algorithms for Inverse Problems in Science and Engineering, 2011

A Moving Balls Approximation Method for a Class of Smooth Constrained Minimization Problems.
SIAM J. Optim., 2010

Gradient-based algorithms with applications to signal-recovery problems.
Proceedings of the Convex Optimization in Signal Processing and Communications., 2010

Lagrangian Multipliers Methods for Convex Programming.
Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems.
IEEE Trans. Image Process., 2009

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems.
SIAM J. Imaging Sci., 2009

A convex optimization approach for minimizing the ratio of indefinite quadratic functions over an ellipsoid.
Math. Program., 2009

Projected subgradient methods with non-Euclidean distances for non-differentiable convex minimization and variational inequalities.
Math. Program., 2009

Foreword: Special issue on nonlinear convex optimization and variational inequalities.
Math. Program., 2009

A fast Iterative Shrinkage-Thresholding Algorithm with application to wavelet-based image deblurring.
Proceedings of the IEEE International Conference on Acoustics, 2009

A Minimax Chebyshev Estimator for Bounded Error Estimation.
IEEE Trans. Signal Process., 2008

Iterative Minimization Schemes for Solving the Single Source Localization Problem.
SIAM J. Optim., 2008

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

Nonmonotone projected gradient methods based on barrier and Euclidean distances.
Comput. Optim. Appl., 2007

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., 2006

Interior Gradient and Proximal Methods for Convex and Conic Optimization.
SIAM J. Optim., 2006

On semidefinite bounds for maximization of a non-convex quadratic objective over the <i>l<sub>1</sub> </i> unit ball.
RAIRO Oper. Res., 2006

A Linearly Convergent Dual-Based Gradient Projection Algorithm for Quadratically Constrained Convex Minimization.
Math. Oper. Res., 2006

Clustering with Entropy-Like <i>k</i>-Means Algorithms.
Proceedings of the Grouping Multidimensional Data - Recent Advances in Clustering, 2006

Interior projection-like methods for monotone variational inequalities.
Math. Program., 2005

Data Driven Similarity Measures for <i>k</i>-Means Like Clustering Algorithms.
Inf. Retr., 2005

Interior Gradient and Epsilon-Subgradient Descent Methods for Constrained Convex Minimization.
Math. Oper. Res., 2004

A conditional gradient method with linear rate of convergence for solving convex linear systems.
Math. Methods Oper. Res., 2004

Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems.
SIAM J. Control. Optim., 2003

Mirror descent and nonlinear projected subgradient methods for convex optimization.
Oper. Res. Lett., 2003

Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems.
Optim. Methods Softw., 2003

Entropic proximal decomposition methods for convex programs and variational inequalities.
Math. Program., 2001

Global Optimality Conditions for Quadratic Optimization Problems with Binary Constraints.
SIAM J. Optim., 2000

Lagrangian Duality and Related Multiplier Methods for Variational Inequality Problems.
SIAM J. Optim., 2000

A probabilistic result for the max-cut problem on random graphs.
Oper. Res. Lett., 2000

Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels.
Math. Oper. Res., 1999

A Logarithmic-Quadratic Proximal Method for Variational Inequalities.
Comput. Optim. Appl., 1999

An Interior Proximal Algorithm and the Exponential Multiplier Method for Semidefinite Programming.
SIAM J. Optim., 1998

Sensitivity analysis for a class of robotic grasping quality functionals.
Robotica, 1998

Convergence of Proximal-Like Algorithms.
SIAM J. Optim., 1997

Experimental validation of an optimization formulation of the human grasping quality sense.
J. Field Robotics, 1997

A Conjugate Duality Scheme Generating a New Class of Differentiable Duals.
SIAM J. Optim., 1996

Nonlinear rescaling and proximal-like methods in convex optimization.
Math. Program., 1996

Hidden convexity in some nonconvex quadratically constrained quadratic programming.
Math. Program., 1996

Convergence Rate Analysis of Nonquadratic Proximal Methods for Convex and Linear Programming.
Math. Oper. Res., 1995

Toeard a formulation of the human grasping quality sense.
J. Field Robotics, 1995

A proximal-based decomposition method for convex minimization problems.
Math. Program., 1994

Entropy-Like Proximal Methods in Convex Programming.
Math. Oper. Res., 1994

Convergence of best phi-entropy estimates.
IEEE Trans. Inf. Theory, 1993

Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions.
SIAM J. Optim., 1993

Entropic Proximal Mappings with Applications to Nonlinear Programming.
Math. Oper. Res., 1992

Portfolio theory for the recourse certainty equivalent maximizing investor.
Ann. Oper. Res., 1991

Upper Bounds on the Expected Value of a Convex Function Using Gradient and Conjugate Function Information.
Math. Oper. Res., 1989

Penalty Functions and Duality in Stochastic Programming Via ϕ-Divergence Functionals.
Math. Oper. Res., 1987

Rate distortion theory with generalized information measures via convex programming duality.
IEEE Trans. Inf. Theory, 1986