Neural Compression — Lecture 02.1 — Theoretical Bounds for Lossless Compression
Channel: Tübingen Machine Learning
Date: 2023-06-02

Third video of the course "Data Compression With and Without Deep Probabilistic Models" by Prof. Robert Bamler at University of Tübingen (summer term of 2023).

Playlist for entire course: https://www.youtube.com/playlist?list=PL05umP7R6ij0KTBVxk00MKoQRMLTWUJh-
Course website (no login required): https://robamler.github.io/teaching/compress23
Lecture notes: https://robamler.github.io/teaching/compress23/lecture-notes-02.pdf
Problem Set: https://robamler.github.io/teaching/compress23/problem-set-02.zip
Solutions to Problem Set: https://robamler.github.io/teaching/compress23/problem-set-02-solutions.zip

KM-Theorem in Professor Jeff Miller's video series on data compression: https://www.youtube.com/watch?v=yHw1ka-4g0s&list=PLE125425EC837021F&index=14

Video Chapters:
0:00 Welcome
0:22 Recap from last video
2:11 Goal of this video
3:48 Kraft-McMillan Theorem: statement
5:36 Corollary
6:27 Lemma
7:29 Proof of part (a) of the KM Theorem
12:00 Proof of part (b) of the KM Theorem
14:49 Example
17:35 Outlook

© Robert Bamler / University of Tübingen, 2023 CC BY-NC-SA 3.0