ECE599-005: Convex Optimization


Course Information Grading TA | Announcements | Course Description | Prerequisites | Textbook |  Course Schedule |  Topics | Homework  | Grading | Exams

Spring 2016
School of Electrical Engineering and Computer Science
Oregon State University


Course Information

Instructor:

Dr. Raviv Raich

Office:

Kelley Engineering Center 3009

Email:


* Kindly use this email address (and not the onid email address)

Classroom:

STAG 262

Time:

MWF  9:00AM -9:50AM

Office hours:

Thu. 4-5, Fri. 4-5


Grading TA

Grading TA:

NA

TA Office:

NA

TA Office hours:

NA


Announcements


Course Description

This course will introduce the fundamental concepts, theories of convex optimization, and the algorithmic solutions as well as applications to many research disciplines including signal processing, networking, communication, and machine learning.  Emphasis will be on (i) optimality conditions, (ii) algorithms and convergence analysis, and (iii) applications.  


Policy


Prerequisites

Strong mathematical background, especially in linear algebra and advanced calculus.


Textbook

Convex Optimization by Stephen Boyd & Lieven Vandenberghe, Cambridge Press


Course Schedule

NOTE: Course Schedule Subject to Change based on Material Pace.

Week #
Book Sections
1
Chapter 2
2
Chapter 2, Chapter 3
3
Chapter 3
4
Chapter 4
5
Chapter 4, Chapter 5
6
Chapter 5
7
Chapter 5, Chapter 9
8
Chapter 9
9
Chapter 10, Chapter 11
10
Chapter 11

Topics


Homework & Solutions

Notice

Efforts on homework should be individual based on the material in class and in the book.  Students who copy from the solution manual, past solutions, or other students, will face disciplinary actions. Any use of the solution manual is unacceptable.



Homework1: HW1.pdf    (due April 8, 2016)     HW1 Solution

Homework2: HW2.pdf    (due April 18, 2016)  
HW2 Solution   

Homework3: HW3.pdf    (due April 29, 2016)  
HW3 Solution     

Homework4: HW4.pdf    (due May 13, 2016)    HW4 Solution   

Homework5: HW5.pdf    (due May 30, 2016)     

Homework6: HW6.pdf    (due May 3, 2016)
    

Grading Policy

The final grade for this class will be determined based on

HW

20%

Midterm (48 hours take-home)

40%

Final

40%

Slack Variable

10%

The final grade will be based on the total number of points accumulated at the end of the term


Exams

Midterm:

48-hour take-home exam      
May 20, 2016

Final exam:

Tue. 12:00pm (noon)
June 7, 2016