His primary areas of study are Mathematical optimization, Nonlinear programming, Constrained optimization, Gradient method and Nonlinear system. José Mario Martínez studied Mathematical optimization and Applied mathematics that intersect with Iterative method. His Nonlinear programming research integrates issues from Karush–Kuhn–Tucker conditions, Theory of computation, Limit point, Constant and Augmented Lagrangian method.
His biological study spans a wide range of topics, including Thin film and Feasible region. His studies in Gradient method integrate themes in fields like Line search and Conjugate gradient method. José Mario Martínez interconnects Computational chemistry and van der Waals force in the investigation of issues within Type.
José Mario Martínez mostly deals with Mathematical optimization, Nonlinear programming, Applied mathematics, Constrained optimization and Nonlinear system. The study incorporates disciplines such as Numerical analysis, Stationary point and Trust region in addition to Mathematical optimization. His Nonlinear programming study also includes
José Mario Martínez brings together Applied mathematics and Simple to produce work in his papers. José Mario Martínez has researched Constrained optimization in several fields, including Regularization, Hessian matrix, Lagrange multiplier and Gradient method. His Nonlinear system research includes elements of Linear system and System of linear equations.
José Mario Martínez mainly focuses on Mathematical optimization, Applied mathematics, Regularization, Minification and Nonlinear programming. His work on Function minimization as part of his general Mathematical optimization study is frequently connected to Subject, thereby bridging the divide between different branches of science. The concepts of his Applied mathematics study are interwoven with issues in Temperature control, Quadratic equation, Continuous derivative, Symbolic convergence theory and Nonlinear system.
The various areas that José Mario Martínez examines in his Regularization study include Stationary point, Constrained optimization and Unconstrained optimization. His Minification study also includes fields such as
His primary areas of investigation include Nonlinear programming, Regularization, Mathematical optimization, Minification and Unconstrained optimization. His research in Nonlinear programming intersects with topics in Algorithm, Augmented Lagrangian method, Lipschitz continuity and Constrained optimization. His study in Constrained optimization is interdisciplinary in nature, drawing from both Optimization algorithm and Point.
His work on Solver and Packing problems as part of general Mathematical optimization research is frequently linked to Ellipsoid, bridging the gap between disciplines. As part of one scientific family, José Mario Martínez deals mainly with the area of Minification, narrowing it down to issues related to the Hessian matrix, and often Newton's method. His research investigates the connection between Unconstrained optimization and topics such as Combinatorics that intersect with issues in Rate of convergence, Quadratic equation, Numerical analysis and Critical point.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
PACKMOL: a package for building initial configurations for molecular dynamics simulations.
Leandro Martínez;Ricardo Andrade;Ernesto G. Birgin;José Mario Martínez.
Journal of Computational Chemistry (2009)
Nonmonotone Spectral Projected Gradient Methods on Convex Sets
Ernesto G. Birgin;José Mario Martínez;Marcos Raydan.
Siam Journal on Optimization (1999)
Packing optimization for automated generation of complex system's initial configurations for molecular dynamics and docking.
José Mario Martínez;Leandro Martínez.
Journal of Computational Chemistry (2003)
On Augmented Lagrangian Methods with General Lower-Level Constraints
R. Andreani;E. G. Birgin;J. M. Martínez;M. L. Schuverdt.
Siam Journal on Optimization (2007)
A Spectral Conjugate Gradient Method for Unconstrained Optimization
E. G. Birgin;J. M. Martínez.
Applied Mathematics and Optimization (2001)
Estimation of the Optical Constants and the Thickness of Thin Films Using Unconstrained Optimization
Ernesto G Birgin;Ivan Chambouleyron;José Mario Martínez.
Journal of Computational Physics (1999)
Algorithm 813: SPG—Software for Convex-Constrained Optimization
Ernesto G. Birgin;José Mario Martínez;Marcos Raydan.
web science (2001)
Spectral residual method without gradient information for solving large-scale nonlinear systems of equations
William La Cruz;José Mario Martínez;Marcos Raydan.
Mathematics of Computation (2006)
Augmented Lagrangian methods under the constant positive linear dependence constraint qualification
R. Andreani;E. G. Birgin;J. M. Martínez;M. L. Schuverdt.
Mathematical Programming (2007)
Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients
Ernesto G. Birgin;José Mario Martínez.
Computational Optimization and Applications (2002)
Profile was last updated on December 6th, 2021.
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Texas A&M University
Chinese Academy of Sciences
Instituto Nacional de Matemática Pura e Aplicada
University of Córdoba
Nanzan University
Hong Kong Polytechnic University
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