Introduction to Big Data Algorithms

Schedule

Date Topic Material Further Reading
03.03. Preliminary Meeting / Probability Theory Slides Introduction Slides Probability Theory
05.03. Probability Theory Slides Probability Theory
10.03. Probability Theory / Discussion of Homework Slides Probability Theory
12.03. Streaming Model / Reservoir Sampling Handwritten notes Lecture notes by Ali Vakilian
17.03. Reservoir Sampling / Median Estimation Handwritten notes Lecture notes by Ali Vakilian Lecture notes by Ali Vakilian
19.03. Discussion of Homework Handwritten notes
24.03. Morris Counter / Variance Reduction Handwritten notes Lecture notes by Ali Vakilian Lecture notes by Amit Chakrabarti
26.03. No class
14.04. Median Trick / Distinct Elements Handwritten notes Lecture notes by Ali Vakilian Lecture notes by Amit Chakrabarti
16.04. Distinct Elements / Majority Element Handwritten notes Lecture notes by Amit Chakrabarti Lecture notes by Ali Vakilian
21.04. Frequent Elements (Misra Gries) Handwritten notes Lecture notes by Ali Vakilian
23.04. Discussion of Homework
28.04. Count-Min Sketch Handwritten notes Lecture notes by Ali Vakilian
30.04. Discussion of Homework Handwritten notes
05.05. Multiplicative Spanners Lecture notes
07.05. Multiplicative Spanners Lecture notes
12.05. Multiplicative Spanners Lecture notes
19.05. More Spanner Constructions Handwritten notes [Dor, Halperin, Zwick 1997]
21.05. Discussion of Homework
28.05. Karger's Contraction Algorithm Slides Lecture Notes by Luca Trevision (Section 13.1.2)
02.06. Cut Sparsification Handwritten notes
09.06. Cut Sparsification Handwritten notes
11.06. Cut Sparsification
16.06. Discussion of Homework
18.06. Q&A Session
23.06. Exam

Homework Problems

Problem Set