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Sublinear Time Algorithms for Estimating Edit Distance

Offered By: Simons Institute via YouTube

Tags

Sublinear Algorithms Courses Information Theory Courses Randomized Algorithms Courses Computational Complexity Courses Dynamic programming Courses Approximation Algorithms Courses

Course Description

Overview

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Explore a comprehensive lecture on sublinear time algorithms for estimating edit distance, presented by Barna Saha from UC San Diego as part of the Sublinear Algorithms Boot Camp at the Simons Institute. Delve into advanced computational techniques that aim to efficiently approximate the edit distance between strings in less than linear time. Gain insights into the latest research and methodologies in this crucial area of computer science, which has applications in bioinformatics, natural language processing, and data analysis. Over the course of 68 minutes, examine the theoretical foundations, practical implementations, and potential future directions of these innovative algorithms.

Syllabus

Sublinear Time Algorithms for Estimating Edit Distance


Taught by

Simons Institute

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