Credits: 5

Schedule: 11.09.2019 - 17.10.2019

Contact information for the course (applies in this implementation): 

Lecturer: prof. Sergiy A. Vorobyov, T-talo, Office: B350

TA: Mr. Endrit Dosti, T-talo, Office: B349 


Teaching Period (valid 01.08.2018-31.07.2020): 

I, 2018 - 2019, 2019 - 2020 (autumn)

Learning Outcomes (valid 01.08.2018-31.07.2020): 

Students will be introduced to and trained to use the tools to recognize convex optimization problems that arise in engineering, scince, economics. They will be introduced to the basic theory of such problems, concentrating on results that are useful in computation. The will also be introduced to basic formats of convex optimization problems that are needed as an input form for convex optimization solvers, such as CVX, and will learn how to use CVX.

Content (valid 01.08.2018-31.07.2020): 

Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs. Semidefinite programming. Solvers.

Details on the course content (applies in this implementation): 

Catalog description

• Concentrates on recognizing and solving convex optimization problems that arise in engineering practice.

• Convex sets, functions, and optimization problems.

• Basics of convex analysis.

• Least-squares, linear and quadratic programs.

• Semidefinite programming.

• Minimax, extremal volume, and other problems.

• Optimality conditions, duality theory, theorems of alternative, and applications.

• Introduction to interior-point methods.

• Applications to many areas of engineering and science (signal processing, digital and analog circuit design, statistics, estimation theory, digital communications and networking, etc.).

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Lectures, exercises, assignments.

Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation): 

Requirements:

• 5 homework assignments (3+2 by the course portions). Homework will normally be assigned on Wendsday and will be due in 2 weeks.

• Final exam. The format is an in-class 2-3 hours exam. For part 1 of the course a test 1 hour 45 minutes in class. We will accommodate your schedule if you cannot take the exams at the scheduled time.

Grading: 

Homeworks: 60% for Part 1 overall grade and 40% for Part 2 overall grade. Test: 40% for Part 1, Exam: 60% for Part 2. These weights are approximate; we reserve the right to change them later; can be also discussed with you.

Workload (valid 01.08.2018-31.07.2020): 

Lectures, excercises, and exams approximately 30 h, assignments and independent studying approximately 103 h, total 133 h

Attendance in some contact teaching may be compulsory.

Details on calculating the workload (applies in this implementation): 

2 lectures every week. lectures are combined with problem solving sessions. Time required for solving home works approximately meets the total time of lecture hours 

Details on the course materials (applies in this implementation): 

Textbook and optional references

• Stephen Boyd; Lieven Vandenberghe, Convex Optimization (Textbook!)

• Ben-Tal and Nemirovski, Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering Applications

• Nesterov, Introductory Lectures on Convex Optimization: A Basic Course

• Ruszczynski, Nonlinear Optimization

• Borwein & Lewis, Convex Analysis and Nonlinear Optimization

• Jon Dattorro, Convex Optimization & Euclidean Distance Geometry

Substitutes for Courses (valid 01.08.2018-31.07.2020): 

ELEC-E5421 Convex Optimizaton for Engineers P

Course Homepage (valid 01.08.2018-31.07.2020): 

https://mycourses.aalto.fi/course/search.php?search=elec-e5422

Prerequisites (valid 01.08.2018-31.07.2020): 

Recommended a course on Linear Algebra or Matrix Computations.

Grading Scale (valid 01.08.2018-31.07.2020): 

0...5

Registration for Courses (valid 01.08.2018-31.07.2020): 

In WebOodi

Further Information (valid 01.08.2018-31.07.2020): 

 

Language class 3: English

Details on the schedule (applies in this implementation): 

ELEC-E5422: Convex Optimization I (5 cr.)

11.09 - 17.10.2019 every Wed. & Thur.

Wed. 9:15am - 11:00am: R037/AS6 

Thur. at 12:15 - 2:00pm: R037/AS1


ELEC-E5422: Convex Optimization II (5 cr.)

30.10 - 11.12.2018 every Wed. & Thur.

Wed. 9:15am - 11:00am: R030/T6 

Thur. at 12:15 - 2:00pm: R030/T5

Description

Registration and further information