Hybrid Toolbox for Matlab Alberto Bemporad http://www.dii.unisi.it/hybrid COHES Group Control and Optimization of Hybrid and Embedded Systems

Source URL: cse.lab.imtlucca.it

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

Offer of Complimentary Software License(s) Hello, MathWorks is pleased to support the DNA Data Bank of Japan Data Analytics Challenge. MathWorks will provide software, training, and access to MathWorks engineering mentor

Source URL: www.ddbj.nig.ac.jp

• Software
• Application software
• Mathematical software
• Cross-platform software
• Array programming languages
• Computer algebra systems
• Optimization Toolbox
• MathWorks
• MATLAB
• Feature Selection Toolbox

Mathematical Optimization at BASF - A Quarter Century and More... Josef Kallrath BASF SE Scientific Computing GMC/MS-B009, 67056 Ludwigshafen, Germany e-mail:

Source URL: or2015.univie.ac.at

• Mathematical optimization
• Numerical analysis
• Operations research
• Mathematics
• Mathematical analysis
• Mathematical modeling
• Computer algebra systems
• Global optimization
• Mathematical model
• Nl
• Linear programming
• Optimization Toolbox

CS168: The Modern Algorithmic Toolbox Lecture #5: Gradient Descent Basics Tim Roughgarden & Gregory Valiant∗ April 11,

Source URL: theory.stanford.edu

• Mathematical analysis
• Numerical analysis
• Mathematics
• Differential calculus
• Rates
• Vector calculus
• Convex analysis
• Gradient descent
• Convex optimization
• Mathematical optimization
• Derivative
• Normal

CS168: The Modern Algorithmic Toolbox Lecture #6: Stochastic Gradient Descent and Regularization Tim Roughgarden & Gregory Valiant∗ April 13, 2016

Source URL: theory.stanford.edu

• Statistics
• Numerical analysis
• Mathematics
• Computational statistics
• Regression analysis
• Econometrics
• Convex optimization
• Estimation theory
• Stochastic gradient descent
• Gradient descent
• Linear regression
• Mathematical optimization

Integer Optimization Toolbox Pooya Ronagh∗ August 13, 2013 In what follows, we explain how the Integer Optimization Toolbox approaches the problem of minimization of a (low degree) polynomial over an integer lattice. I

Source URL: www.1qbit.com

CS168: The Modern Algorithmic Toolbox Lecture #15: Gradient Descent Basics Tim Roughgarden & Gregory Valiant May 18,

Source URL: web.stanford.edu

• Numerical analysis
• Mathematical analysis
• Mathematical optimization
• Convex analysis
• Operations research
• Convex optimization
• Gradient descent
• Derivative
• Convex function
• Linear programming
• Gradient boosting
• FrankWolfe algorithm

Dynamic optimization: Continuous-time DSGE Olaf Posch () Summer course 2010 Course objective. This course provides a toolbox for solving continuous-time dynamic optimization problems in (stochastic) econ

Source URL: www.oposch.com

• Systems theory
• Control theory
• Equations
• Dynamic programming
• Optimal control
• Macroeconomic model
• Bellman equation
• Dynamic stochastic general equilibrium
• Stochastic
• Mathematical optimization
• Macroeconomics
• Operations research

Dynamic Optimization Olaf Posch () Summer course 2009 Course objective. This course provides a toolbox for solving dynamic optimization problems in economic models. In particular, we review the mathemati

Source URL: www.oposch.com