Explore a groundbreaking approach to computing edit distance in near-linear time through this 26-minute IEEE conference talk by Columbia University researchers Alexandr Andoni and Negev Shekel Nosatzki. Delve into the problem setup, potential solutions, and the innovative approach that achieves this computational feat. Gain insights into the underlying data structure and its guarantees, understanding why this method works and its implications for algorithmic efficiency.
Edit Distance in Near-Linear Time - It’s a Constant Factor
Overview
Syllabus
Introduction
Problem set up
What can be done
Approach
Why
Solution
Data Structure
Guarantees
Taught by
IEEE FOCS: Foundations of Computer Science
Tags
Related Courses
-
Sublinear Algorithms for Gap Edit Distance
-
Constant Factor Approximations to Edit Distance in Nearly Linear Time
-
Near-Linear Size Hypergraph Cut Sparsifiers
-
Algorithms and Hardness for Linear Algebra on Geometric Graphs
-
List Decodable Mean Estimation in Nearly Linear Time
-
Parallel Reachability in Almost Linear Work and Square Root Depth
