A SEMIDEFINITE HIERARCHY FOR CONTAINMENT OF SPECTRAHEDRA KAI KELLNER, THORSTEN THEOBALD, AND CHRISTIAN TRABANDT Abstract. A spectrahedron is the positivity region of a linear matrix pencil and thus the feasible set of a

Source URL: www.math.uni-frankfurt.de

CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

Source URL: theory.stanford.edu

• Mathematical optimization
• Numerical analysis
• Mathematical analysis
• Operations research
• Linear programming
• Convex optimization
• Convex analysis
• Ellipsoid method
• Feasible region
• Convex function
• Linear inequality
• Candidate solution

Neuroevolutionary Constrained Optimization for Content Creation Antonios Liapis, Georgios N. Yannakakis, Member, IEEE and Julian Togelius, Member, IEEE Abstract— This paper presents a constraint-based procedural conten

Source URL: antoniosliapis.com

• Mathematical optimization
• Operations research
• Cybernetics
• Applied mathematics
• Mathematical analysis
• Systems science
• Candidate solution
• Constraint
• Genetic algorithm
• Spaceship
• Feasible region
• Interplanetary Transport System

Interactive Design Exploration for Constrained Meshes Bailin Deng∗, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg, Mark Pauly Computer Graphics and Geometry Laboratory, EPFL, CH-1015 Lausanne, Switz

Source URL: www.bdeng.me

• Mathematical optimization
• Mathematical analysis
• Analysis
• Mathematics
• Shape optimization
• Constraint
• Constrained optimization
• Feasible region
• Optimization problem
• Lagrange multiplier
• Penalty method

Microsoft Word - NEW06.docx

Source URL: agecon2.tamu.edu

• Operations research
• Mathematical optimization
• Linear programming
• Mathematical analysis
• Feasible region
• Constraint
• Analysis
• Mathematics
• Simplex algorithm
• Constraint satisfaction

CS261: A Second Course in Algorithms Lecture #8: Linear Programming Duality (Part 1)∗ Tim Roughgarden† January 28,

Source URL: theory.stanford.edu

• Mathematical optimization
• Operations research
• Convex optimization
• Linear programming
• Mathematical analysis
• Duality
• Constraint
• Feasible region
• Semidefinite programming
• Lagrangian relaxation

CS261: A Second Course in Algorithms Lecture #7: Linear Programming: Introduction and Applications∗ Tim Roughgarden† January 26, 2016

Source URL: theory.stanford.edu

• Mathematical optimization
• Operations research
• Numerical analysis
• Mathematical analysis
• Linear programming
• Convex optimization
• Combinatorial optimization
• Feasible region
• Duality
• Linear regression
• Candidate solution
• Linear-fractional programming

Geometric Optimization Equinoctial School on Geometric Computing ETH Zurich, 15. { 26. SeptemberBernd Gartner

Source URL: people.inf.ethz.ch

• Mathematical optimization
• Operations research
• Linear programming
• Convex optimization
• Combinatorial optimization
• Simplex algorithm
• Feasible region
• Simplex
• Polytope
• Quadratic programming
• Constraint
• Bounding sphere

Microsoft Word - NEW02.docx

Source URL: agecon2.tamu.edu

• Operations research
• Mathematical optimization
• Integer programming
• Linear programming
• Feasible region
• Constraint

Interactive Design Exploration for Constrained Meshes Bailin Deng∗, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg, Mark Pauly Computer Graphics and Geometry Laboratory, EPFL, CH-1015 Lausanne, Switz

Source URL: lgg.epfl.ch

• Mathematical optimization
• Shape optimization
• Constraint
• Constrained optimization
• Feasible region
• Optimization problem
• Lagrange multiplier
• Penalty method