Course Identification

Title:

Convex Optimization

Code:

20184172

Lecturers and Teaching Assistants

Lecturers:

Dr. Meirav Galun

TA's:

Dr. Nadav Dym

Course Schedule and Location

Year:

2018

Semester:

Second Semester

When / Where:

Thursday, 09:15 - 11:00, Jacob Ziskind Building, Rm 155

First Lecture:

15/03/2018

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: Lecture; Elective; 2.00 points

Comments

N/A

Prerequisites

No

Restrictions

Participants:

50

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

Final:

100%

Evaluation Type

Examination

Scheduled date 1

Date / due date

12/07/2018

Location

Ziskind, Rm 1

Time

0900-1300

Remarks

N/A

Scheduled date 2

Date / due date

N/A

Location

N/A

Time

-

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

5

Syllabus

Convex optimization methods are in the core of modern science. This course will provide an extended introduction covering theoretical as well as practical (hands-on) aspects of the theory and algorithms.

Learning Outcomes

Upon successful completion of this course students should be able to apply practical convex optimization methods to research in computer vision, computer graphics, data analysis, and machine learning.

Reading List

N/A

Website

N/A