Topics in Kolmogorov Complexity, Seminar 236804


Kolmogorov, Andrey Nikolayevich



Instructor:

Ran El-Yaniv
Office: 526, Phone: 829-4328, Email: rani@cs.technion.ac.il
Office hours: Monday 16:30-17:30
Lecture hour: Sunday 12:30-14:30, Taub 8

Kolgmogorov complexity is a deep and sophisticated theory that provides the means to measure the intrinsic information in objects via their algorithmic description length. It applies to a wide range of areas including theory of computation, combinatorics, inductive reasoning and machine learning. In this seminar we will cover the basics and some applications of Kolmogorov complexity. The main text for this seminar will be An introduction to Kolmogorov complexity and its applications by Li and Vitanyi.

Requirements:

each student is required to give an individual presentation, submit a short article summarizing his/her presentation, read all the seminar articles and background material, and is expected to attend all the classes and contribute to the discussions. All these components will contribute to the seminar?s final mark. Specifically, to get a full mark, students have to successfully complete the following tasks:

Attendance and participation:

Each student is expected to attend all seminar meetings, be involved in other students? presentations, read other students? presentation summaries, and participate in the discussions.

The Lecture program:

All section references in the list below are to the course book: An Introduction to Kolmogorov Complexity and its applications, by Li and Vitanyi, Second edition.

Number

Topic and slides (when available)

Lecturer

Date

Section in the book

0 Overview Ran El-Yaniv . .
1 Introduction as PPT, as PS Asaf Mesika . 1.1, 1.2, 1.4, 1.6, 1.7, 1.11
2 Algorithmic complexity Shimon Landa . 2.1, 2.2, 2.3
3,4 Algorithmic complexity lecture sum, as PS, slides Eitan Joshua . 2.4, 2.5, 2.6, 2.8
5 Algorithmic prefix complexity, lecture sum and slides Yariv Maron 30/4 3.1 - 3.5
6 Algorithmic probability, lecture sum 1, 2, 3 lecture slides Shiri Moran 7/5 4.1, 4.2, 4.3
7 Algorithmic probability Vitali Feldman 14/5 4.5
8 Inductive reasoning, slides , word doc Tzach Livyatan 21/5 5.1, 5.2 5.3
9 Inductive reasoning Davidov Dmitry 4/6 5.4
10 Physics, Information and Computation Dmitry Gavinsky 11/6 8
11 Inductive reasoning Philip Derbeko 18/6 5.5
12 Physics, Information and Computation, as PDF, as PPT Ziv Nevo 25/6 8

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