Algorithms for Big Data (COMPSCI 229r), Lecture 7

Algorithms for Big Data (COMPSCI 229r), Lecture 7 This lecture explores L0 sampling as a foundational primitive for processing streaming graph data. Participants examine algorithms for maintaining sketches under turnstile model updates, effectively addressing connectivity and related graph problems using significantly less space than traditional edge-storing methods.

Algorithms for Big Data (COMPSCI 229r), Lecture 6

Algorithms for Big Data (COMPSCI 229r), Lecture 6 CountMin sketch, point query, heavy hitters, sparse approximation. Scribe: Mien Wang.

Algorithms for Big Data (COMPSCI 229r), Lecture 5

Algorithms for Big Data (COMPSCI 229r), Lecture 5 Analysis of ℓp estimation algorithm via max-stability, deterministic point query via incoherent matrices.

Algorithms for Big Data (COMPSCI 229r), Lecture 4

Algorithms for Big Data (COMPSCI 229r), Lecture 4 P-stable sketch analysis, Nisan's PRG, ℓp estimation for p larger than 2 via max-stability.

Algorithms for Big Data (COMPSCI 229r), Lecture 3

Algorithms for Big Data (COMPSCI 229r), Lecture 3 Necessity of randomized/approximate guarantees, linear sketching, AMS sketch, p-stable sketch for p less than 2.