Augmented Lagrangian Preconditioner for Linear Stability Analysis of incompressible fluid flows on large configurations J.Moulin1, J-L. Pfister1, O.Marquet1, P. Jolivet2 1 Office National d’Etudes et de Recherches Aér

Source URL: www.ljll.math.upmc.fr

Augmented Lagrangian preconditioner for Linear Stability Analysis of the incompressible Navier-Stokes equation Johann Moulin, Jean-Lou Pfister, Olivier Marquet and Pierre Jolivet Linear Stability Analysis is a widely use

Source URL: www.ljll.math.upmc.fr

MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation J¨ org Hendrik Kappes, Stefan Schmidt, and Christoph Schn¨orr Image and Pattern Analysis Group & HCI, University of Heidelberg, Germany, {kappes,schm

Source URL: ipa.iwr.uni-heidelberg.de

Dynamics of Sensor vs. Target Ling Bian Department of Geography, University at Buffalo May 20, 2016 Representation of Spatial Dynamics

Source URL: ncgia.buffalo.edu

• Oceanography
• Fluid dynamics
• Lagrangian analysis
• Velocimetry

Second-order Lagrangians admitting a …rst-order Hamiltonian formalism M. Eugenia Rosado María Departamento de Matemática Aplicada Escuela Técnica Superior de Arquitectura, UPM Avda. Juan de Herrera 4, 28040-Madrid,

Source URL: gigda.ugr.es

• Physics
• Theoretical physics
• Dynamical systems
• Quantum field theory
• Mathematical physics
• Mathematical analysis
• Calculus of variations
• Lagrangian
• Hamiltonian mechanics
• Jet bundle

Geodesics on standard stationary spacetimes and Lagrangian systems Anna Valeria Germinario Dipartimento di Matematica, Universita’ di Bari, Italy

Source URL: xtsunxet.usc.es

• Theoretical physics
• Physics
• Differential geometry
• Theory of relativity
• Geodesic
• Spacetime
• Dynamical systems
• Mathematical analysis
• General relativity
• Finsler geometry
• Closed geodesic
• Differential geometry of surfaces

Grenoble Optimization Day November 5, LJK, Université Joseph Fourier, Grenoble, France How the augmented Lagrangian algorithm can deal with an infeasible convex quadratic optimization problem —

Source URL: bipop.inrialpes.fr

• Numerical analysis
• Mathematical optimization
• Mathematical analysis
• Operations research
• Convex optimization
• Linear programming
• Duality
• FrankWolfe algorithm
• Equation solving
• Algorithm

Dual Decomposition with Many Overlapping Components Andr´e F. T. Martins∗† Noah A. Smith∗ Pedro M. Q. Aguiar‡ M´ario A. T. Figueiredo† ∗ School of Computer Science, Carnegie Mellon University, Pittsburgh, P

Source URL: users.isr.ist.utl.pt

• Mathematical optimization
• Operations research
• Mathematics
• Mathematical analysis
• Convex optimization
• Subgradient method
• Augmented Lagrangian method
• Decomposition method
• Dynamic programming
• Algorithm
• Linear programming

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

247 Eurographics/ ACM SIGGRAPH Symposium on Computer AnimationA. Bargteil and M. van de Panne (Editors) Asynchronous Integration with Phantom Meshes David Harmon† , Qingnan Zhou, and Denis Zorin

Source URL: www.cs.nyu.edu

• Computational chemistry
• Molecular dynamics
• Numerical analysis
• Scientific modeling
• Ordinary differential equations
• Variational integrator
• Geometric integrator
• Numerical methods for ordinary differential equations
• Integrator
• Finite element method
• Lagrangian mechanics
• Energy drift