FRTN50 - Optimization for Learning
The course program contains the schedule and all relevant information regarding lectures, exercises, content, logistics, deadlines etc. The course program and other course material will be updated when needed.
Our policy is based on our department's general guidelines . The policy can be found in the course program.
Zoom Meeting Invites
See the following Announcement .
Some lecture videos (that are short flipped classroom type videos, not lecture recordings) can be found here.
Intended use: The videos are intended for active listening. This means pausing, skipping 15 s back (or forward) within video to repeat, e.g., an argument, skipping between videos to recall concepts, changing playback speed, and maybe taking notes and verifying calculations while watching.
Lecture videos for the remaining lectures are recorded during live Zoom presentations and can be found here.
- L1 - Convex sets (videos)
- L2 - Convex functions (videos)
- L3 - Subdifferentials and the proximal operator (videos/videos)
- L4 - Conjugate functions and duality (videos/videos)
- L5 - Proximal gradient method - Basics (videos)
- L6 - Least squares (video)
- L7 - Logistic regression (video)
- L8 - Support vector machines (video)
- L9 - Deep learning (video)
- L10 - Convergence rates and proving convergence (videos)
- L11 - Proximal gradient method - Theory (videos)
- L12 - Stochastic gradient descent (videos)
- L13 - Coordinate gradient descent (unfortunately forgot to record Zoom lecture)
- Bonus - Newton's method and quasi-Newton methods
- Bonus - Implicit regularization
- Exercise Compendium (updated: 20-10-07)
- Introduction to Julia
The syllabus page shows a table-oriented view of course schedule and basics of course grading. You can add any other comments, notes or thoughts you have about the course structure, course policies or anything else.
To add some comments, click the 'Edit' link at the top.