Deep learning and continuous optimization

Description
Class meetings: Lecture Thu 14:00-15:30 and Problem-solving class Thu 15:45-16:30. If you have any questions, you can email me to set up an appointment.

Grading: The first half of the course is devoted to continuous optimization. During this part, there will be weekly homework assignments worth a total of 50 points, and a midterm exam in Week 6 worth 50 points. Homework must be submitted electronically within one week to kristof.berczi@ttk.elte.hu. The grade for the first half of the course is based on the total score as follows: 0-39 fail, 40-54 pass, 55-69 satisfactory, 70-84 good, 85+ excellent.

Slides
Week 1
Week 2
Week 3

Week 4
Week 5

Homework
Set 1
Set 2
Set 3

Set 4
Set 5

You can check your results here.

Lecture notes
N. Vishnoi. Algorithms for convex optimization
L.C. Lau. Convexity and optimization
S. Bubeck. Convex Optimization: Algorithms and Complexity
S. Boyd, L. Vandenberghe. Convex Optimization