Kolmogorov complexity 24/25

Classes

Lectures + seminar: Friday 18h10 -- 21h00 in Pokrovkaya room G405 (electives-shedule) and in zoom. The teacher is Bruno Bauwens.

Telegram group for announcements and discussions invite link.

Course Materials

Rec	Summary	Notes	Problem list	Solutions
04.10	Course overview, (universal) Turing machines, computable and non-computable sets and functions. slides.pdf	ch00 ch01	sem01 update 11.10	sol01
11.10	Optimality of Solomonoff induction. See Vitanyi chapter 5.1--5.2 for background. slides.pdf	ch02 ch03	sem02 update 26.10 (Huawei sem02)	sol02
25.10	Minimizing loss according to unknown computable measure (non-responsive systems). Merhav-Feder and Helinger bounds for Bayesian mixtures. (The recording failed.)	ch04	see notes ch04
01.11	Minimizing loss in responsive systems. Self-optimizing strategies in sets of environments. If there exists a self-optimizing strategy, then a Bayesian mixture over all environments in a countable set is self optimizing. A variant with algorithmic probability. recording 2nd part	ch05	sem04
08.11	Plain Kolmogorov complexity, simple properties, Godel-incompleteness, upper bounds, symmetry of information (see also notes)	05sl	sem05	sol05
15.11	Prefix Kolmogorov complexity 3 definitions, upper bounds, symmetry of information.	06sl	sem06
22.11	Information distance, clustering by compression, google distance. Seminar: incompressibility method	07sl	sem07
06.12	Algorithmic statistics, overview paper (notes later)		sem08
13.12	Colloquium: 17h00 room G116 (from 18h in G406). Questions and rules.

Homeworks

Deadlines: every 2 weeks, before the lecture at 18h00. Submit in pdf or fotos of handwritten to brbauwens@gmail.com with the subject line starting with KOLM-HW. Link with results will be here.

Tasks are in the problem lists from the seminar. Deadlines: problem lists 1 and 2: at the start of 3rd lecture, lists 3 and 4 at the start of the 5th lecture, etc.

Late policy: 1 homework can be submitted at most 24h late without explanations.

References

See notes00.pdf above.

Grading

Final score = 0.35 * [score homework] + 0.35 * [score colloquium] + 0.3 * [score exam] 

Some homework assignments contain extra problems. Each solution of an extra problem will give 1 extra points on the final exam (which is graded out of 10). There will be around 10 extra problems. Rounding is applied only when the final score is transferred to the official grade. Arithmetic rounding is used. Autogrades. If only 6/10 for the exam is needed to get a final score of 10/10, then this will be given automatically.

Colloquium and exam

Colloquium: in the middel of December, a list with about 10 questions will be provided.

Exam: Problems similar to the homework. You may use main references, lecture notes, and handwritten notes.

Office hours

Bruno Bauwens: Tuesday 12h -- 20h. Wednesday 16h -- 18h. Friday 11h -- 17h. Better send me an email in advance.