<--- Back to Details
First PageDocument Content
Mathematics / Global optimization / Maximum a posteriori estimation / Genetic algorithm / Estimation of distribution algorithm / Multidisciplinary design optimization / No free lunch in search and optimization / Combinatorial optimization / Surrogate model / Mathematical optimization / Statistics / Applied mathematics
Date: 2014-07-01 08:28:02
Mathematics
Global optimization
Maximum a posteriori estimation
Genetic algorithm
Estimation of distribution algorithm
Multidisciplinary design optimization
No free lunch in search and optimization
Combinatorial optimization
Surrogate model
Mathematical optimization
Statistics
Applied mathematics

Optimizing Without Derivatives: What Does the No Free Lunch Theorem Actually Say? Loris Serafino

Add to Reading List

Source URL: www.ams.org

Download Document from Source Website

File Size: 307,66 KB

Share Document on Facebook

Similar Documents

Classroom Voting Questions: Multivariable Calculus 15.2 Optimization 1. Estimate the global maximum and minimum of the functions whose level curves are given below. How many times does each occur?

Classroom Voting Questions: Multivariable Calculus 15.2 Optimization 1. Estimate the global maximum and minimum of the functions whose level curves are given below. How many times does each occur?

DocID: 1vnbq - View Document

Bandits, Global Optimization, Active Learning, and Bayesian RL – understanding the common ground Marc Toussaint Machine Learning & Robotics Lab – University of Stuttgart  Aut

Bandits, Global Optimization, Active Learning, and Bayesian RL – understanding the common ground Marc Toussaint Machine Learning & Robotics Lab – University of Stuttgart Aut

DocID: 1vg3W - View Document

Journal of Global Optimization manuscript No. (will be inserted by the editor) Stabilizer-based symmetry breaking constraints for mathematical programs Leo Liberti · James Ostrowski

Journal of Global Optimization manuscript No. (will be inserted by the editor) Stabilizer-based symmetry breaking constraints for mathematical programs Leo Liberti · James Ostrowski

DocID: 1v0h9 - View Document

Bandits, Global Optimization, Active Learning, and Bayesian RL – understanding the common ground Marc Toussaint Machine Learning & Robotics Lab – University of Stuttgart  Mac

Bandits, Global Optimization, Active Learning, and Bayesian RL – understanding the common ground Marc Toussaint Machine Learning & Robotics Lab – University of Stuttgart Mac

DocID: 1uWH2 - View Document

Global Optimization of a Magnetic Lattice using Genetic Algorithms Lingyun Yang September 3, 2008

Global Optimization of a Magnetic Lattice using Genetic Algorithms Lingyun Yang September 3, 2008

DocID: 1uOee - View Document