# Convex Analysis and Optimization

Min common/max crossing problems. See Lectures 8–9 for more information. (Image by MIT OpenCourseWare.)

### Instructor(s)

Prof. Dimitri Bertsekas

### MIT Course Number

6.253

### As Taught In

Spring 2012

### Level

Graduate

###

Some Description
Instructor(s) | Prof.
As Taught In | Spring 2002
Course Number | 2.24
Level | Undergraduate/Graduate
Features | Lecture Notes, Student Work

## Course Description

## Course Features

- Lecture notes
- Assignments: problem sets with solutions
- Exams and solutions

## Course Description

This course will focus on fundamental subjects in convexity, duality, and convex optimization algorithms. The aim is to develop the core analytical and algorithmic issues of continuous optimization, duality, and saddle point theory using a handful of unifying principles that can be easily visualized and readily understood.

## Other Versions

## Other OCW Versions

Archived versions:

- 6.253 Convex Analysis and Optimization (Spring 2010)
- 6.253 Convex Analysis and Optimization (Spring 2004)

## Related Content

## Course Collections

See related courses in the following collections:

### Find Courses by Topic

- Computer Science > Algorithms and Data Structures
- Mathematical Analysis

Dimitri Bertsekas. 6.253 Convex Analysis and Optimization. Spring 2012. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.

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