<--- Back to Details
First PageDocument Content
Mathematical optimization / Numerical analysis / Mathematical analysis / Operations research / Linear programming / Convex optimization / Convex analysis / Ellipsoid method / Feasible region / Convex function / Linear inequality / Candidate solution
Date: 2016-06-04 09:49:43
Mathematical optimization
Numerical analysis
Mathematical analysis
Operations research
Linear programming
Convex optimization
Convex analysis
Ellipsoid method
Feasible region
Convex function
Linear inequality
Candidate solution

CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

Add to Reading List

Source URL: theory.stanford.edu

Download Document from Source Website

File Size: 305,83 KB

Share Document on Facebook

Similar Documents

The Ellipsoid Method: A Survey

The Ellipsoid Method: A Survey

DocID: 1rsIC - View Document

CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

DocID: 1rjsj - View Document

CS261: Exercise Set #5 For the week of February 1–5, 2016 Instructions: (1) Do not turn anything in. (2) The course staff is happy to discuss the solutions of these exercises with you in office hours or on Piazza.

CS261: Exercise Set #5 For the week of February 1–5, 2016 Instructions: (1) Do not turn anything in. (2) The course staff is happy to discuss the solutions of these exercises with you in office hours or on Piazza.

DocID: 1qXY7 - View Document

From Convex Optimization to Randomized Mechanisms: Toward Optimal Combinatorial Auctions∗ Shaddin Dughmi† Tim Roughgarden‡

From Convex Optimization to Randomized Mechanisms: Toward Optimal Combinatorial Auctions∗ Shaddin Dughmi† Tim Roughgarden‡

DocID: 1qR3A - View Document

Simple and Fast Inverse Alignment John Kececioglu and Eagu Kim Department of Computer Science, The University of Arizona, Tucson, AZ 85721, USA {kece, egkim}@cs.arizona.edu

Simple and Fast Inverse Alignment John Kececioglu and Eagu Kim Department of Computer Science, The University of Arizona, Tucson, AZ 85721, USA {kece, egkim}@cs.arizona.edu

DocID: 1qOVn - View Document