Theory Seminar - On Linear Data Structures and Matrix Rigidity, Sivaramakrishnan Ramamoorthy
Paul G. Allen School via YouTube
AI, Data Science & Cloud Certificates from Google, IBM & Meta
AI Engineer - Learn how to integrate AI into software applications
Overview
Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Explore a theory seminar on linear data structures and matrix rigidity presented by Sivaramakrishnan Ramamoorthy from the University of Washington. Delve into the equivalence between systematic linear data structures and rectangular rigidity, examine rigidity lower bounds for rank one matrix vectors, and investigate a Cayley graph question related to linear data structures. Learn about upper bounds, algorithmic questions, redundancy, rigidity theorems, query sets, proofs, and open problems in this 55-minute lecture from the Paul G. Allen School, recorded on February 11, 2020 with closed captions available.
Syllabus
Introduction
Linear data structures
Upper bounds
Algorithmic questions
Redundancy
rigidity
theorem
query sets
proof
open problem
Taught by
Paul G. Allen School