Theoretical Computer Science 2022

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Classes

Wednesdays 18:10–21:00, room TBA, zoomlink

Dates and Deadlines

Grading

Grades

Exam: 40%
Homework: 20%
Project: 40%


Course Materials

The main reference for the first 4 lectures is Sipser's book "Introduction to the theory of computation", chapters 1, 2–7.

If you need some background in math, consider these two sources:
Lecture notes: Discrete Mathematics, L. Lovasz, K. Vesztergombi
Лекции по дискретной математике (черновик учебника, in Russian)


Video Summary Notes
19.01 Regular languages
in logarithmic space. See Chapts 6.1-6.2 in foundations of datascience by Avrim Blum and others. Another nice chapter in Tim Roughgarden's lecture notes || Problem set 10
23.11 Finding the frequent items in streams of data: SpaceSaving and Count-Min Sketch. Slides Problem set 11
30.11 Approximation algorithms. Approximate solutions for Vertex Cover, Weighted Vertex Cover, and TSP. Slides. Seminar. Problem set 12
07.12 Colloquium.
14.12 Complexity of clustering: an exact algorithm for maximizing the inter-cluster distance and an approximate algorithm for minimizing the intra-class distance. Sample exam

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Office hours

Person Monday Tuesday Wednesday Thursday Friday
Bruno Bauwens, S834, Zoom 14:00-20:00