This book, developed through class instruction at MIT over the last 15 years, provides an accessible, concise, and intuitive presentation of algorithms for solving convex optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of vi
Algorithms for optimization
โ Scribed by Tim Allan Wheeler; Mykel J. Kochenderfer
- Year
- 2019
- Tongue
- English
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.
In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gra
R users can often solve optimization tasks easily using the tools in the optim function in the stats package provided by default on R installations. However, there are many other optimization and nonlinear modelling tools in R or in easily installed add-on packages. These present users with a bewild