<--- Back to Details
First PageDocument Content
Convex optimization / Operations research / Convex function / Subgradient method / Linear programming / Interior point method / Ellipsoid method / Mathematical optimization / Mathematical analysis / Convex analysis
Date: 2015-05-09 05:30:40
Convex optimization
Operations research
Convex function
Subgradient method
Linear programming
Interior point method
Ellipsoid method
Mathematical optimization
Mathematical analysis
Convex analysis

Add to Reading List

Source URL: www.mat.univie.ac.at

Download Document from Source Website

File Size: 181,44 KB

Share Document on Facebook

Similar Documents

Hausdorff Center for Mathematics, Summer School (May 9–13, 2016) Problems for “Discrete Convex Analysis” (by Kazuo Murota) Problem 1. Prove that a function f : Z2 → R defined by f (x1 , x2 ) = φ(x1 − x2 ) is

DocID: 1vjVY - View Document

How elegant modern convex analysis was influenced by Moreau’s seminal work. Samir ADLY University of Limoges, France

DocID: 1vhAg - View Document

December 8, 2016 Errata to Kazuo Murota, Akiyoshi Shioura, and Zaifu Yang: “Time Bounds for Iterative Auctions: A Unified Approach by Discrete Convex Analysis”

DocID: 1vbMj - View Document

Hausdorff School: Economics and Tropical Geometry Bonn, May 9-13, 2016 Discrete Convex Analysis III: Algorithms for Discrete Convex Functions Kazuo Murota

DocID: 1v6lO - View Document

Operator Splitting Methods for Convex Optimization Analysis and Implementation Goran Banjac St Edmund Hall

DocID: 1v2Df - View Document