Learning Theory

Instructor Nicolas Macris Instructor Ruediger Urbanke
Office INR 134 Office INR 116
Email [email protected] Email [email protected]
       
Teaching Assistant

Farzad Pourkamali

[email protected]

Office  
Teaching Assistant

 

 

Office  
       
Lectures Monday, 08:15 – 10:00 Room INM 202
Exercises Tuesday, 17:15 – 19:00 Room INR 119

Language: English Credits: 4 ECTS Prerequisites:

  • Analysis I, II, III
  • Linear Algebra
  • Machine learning
  • Probability
  • Algorithms (CS-250)

Here is a link to official coursebook information. Homework: Some homework will be graded. Grading: If you do not hand in your final exam your overall grade will be NA. Otherwise, your grade will be determined based on the following weighted average: 10 % for the Homework, 90 % for the Final Exam. For the graded homeworks,  you can discuss the homework with other people. But you have to write down your own solution and note on the first page the set of people that you discussed with.

Special Announcements

Lectures:

Lectures will be in presence on Mondays, from 8:15pm to 10:15pm.

Exercise sessions:

Exercise sessions take place on Tuesdays, from 5pm to 7pm in presence.

Graded homework

The graded homework are collected via this Moodle page. You can either write them by hand and scan or you can use latex: Latex template graded homework. If you cannot compile LaTeX on your own computer, EPFL is providing Overleaf Professional accounts for all students: Overleaf EPFL . With Overleaf you can write and compile LaTeX directly from your web browser. To use the provided template (.tex), you can create a new project and upload the .tex file. 

Final exam

The final exam is a 3 hour open-book on-campus exam (lecture notes, exercices, course material, but no electronic devices), held during the regular exam period. This exam will contribute 90% to the grade.

Topics

Detailed Schedule

See the Moodle page for weekly program and handouts

Textbooks and notes:

  1. Original paper by Jakot et al.
  2. An “easier to read” follow up paper by Arora et al.
  3. A nice blog article by Rajat Vadiraj Dwaraknath