Explore a 19-minute IEEE conference talk on algorithms and hardness for linear algebra on geometric graphs. Delve into K and K-graphs, problem-solving approaches, and the significance of these mathematical concepts. Discover notable results, learn about sparsifiers, and understand the hardness of matrix-vector multiplication. Gain insights into the connection between these topics and Hamming Nearest Neighbor problems. Presented by Josh Alman (Harvard), Timothy Chu (CMU), Aaron Schild (UW), and Zhao Song, this talk offers a concise yet comprehensive overview of advanced concepts in computational geometry and linear algebra.
Algorithms and Hardness for Linear Algebra on Geometric Graphs
Overview
Syllabus
Intro
Examples of K and K -graphs
What problem are we solving?
Why solve these problems (part 2)
Notable Results
How? (Sparsifiers)
How? Hardness for Matrix-Vector Multiplication
Why Hamming Nearest Neighbor?
Taught by
IEEE FOCS: Foundations of Computer Science
