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Course Information
Identification

CS 424: Convex Optimization
 
Description

1. Convex Analysis
a. Sets: Linear, Affine, Conic, and Convex - Primal and dual characterization, Dual cones, and polar sets,
Properties (Topological etc.) of these sets, Separation Theorem b. Functions: Linear, Affine, Conic, and
Convex - Primal and dual characterization, Dual norms, and Conjugates, Properties (Calculus etc.) of
these functions
2. Theory of Convex Optimization
a. Existence, uniqueness, and characterization of optimal solution - KKT conditions etc.
b. Standard forms like Linear, Quadratic, Conic Quadratic, SDP etc. with examples
c. Duality schemes like Lagrange, Conic, Fenchel etc.
 
References

Nemirovski. Lecture Notes on Modern Convex Optimization. Available online, 2005.
Boyd and Vandenberghe: Convex Optimization. Cambridge University Press, 2004.
Bertsekas with Nedic and Ozdaglar: Convex Analysis and Optimization.
Athena Scientific, 2003.
 
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Prerequisites

Desired background for taking the course: Basics of linear algebra and multivariate calculus
 
Other Details

Duration : Full Semester Total Credit : 6
Type : Theory
 
Current Semester (Autumn 2017-18)

Status : Offered Instructor : Prof. Ganesh Ramakrishnan
 
Next Semester (Spring 2017-18)

Status : Not Offered Instructor : ---




Last Modified Date: 15-Jul-2013

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