Applied Algorithms -- Algorithms for Large Data


Lecture hours: Mon 14:00 -- 15:25 and Thu 14:00 -- 15:25
Office hours: Wed 11:00 -- 12:30
Location: SIC 201
Instructor: Nutan Limaye (firstname[AT]cse[DOT]iitb[DOT]ac[DOT]in)

Course Outline

The course outline is sketched out here.

Lecture notes

The course is divided into 4 modules.

Algorithms for problems on large datasets

Math Preliminaries [pdf]

Lecture 1: Introduction [pdf]

Lecture 2: Computing the length of the input (Morris's algorithm) [pdf]

Lecture 3: Counting the number of distinct elements. [pdf]

Lecture 4: Pairwise independence [pdf]

Lecture 5: Frequency moments and computation of F2 [pdf]

Lecture 6: Count-min and count sketches. [pdf]

Lecture 7: Analysis of Count sketch algorithm. [pdf]

Lecture 8: Sampling based approach for distinct elements. [pdf]

Algorithms for problems in linear algebra/geometry

Lecture 9: A brief introduction to Johnson-Linderstrauss Lemma and its versions. [pdf]

Algorithms for large graphs

Information theory for proving lower bounds

Notes will be uploaded soon.

Tutorials, Quizes, and Exams

Will be updated soon.



The style file used for scribe notes is borrowed from Prahladh Harsha.