A Deterministic Theory of Low Rank Matrix Completion

Channel:
United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=iIrgGa1F46c


Duration: 50:30
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11

Sourav Chatterjee (Stanford University)
https://simons.berkeley.edu/node/22589
Graph Limits, Nonparametric Models, and Estimation

The problem of completing a large low rank matrix using a subset of revealed entries has received much attention in the last ten years. I will give a necessary and sufficient condition, stated in the language of graph limit theory, for a sequence of matrix completion problems with arbitrary missing patterns to be asymptotically solvable. I will also present an algorithm that is able to approximately recover the matrix whenever recovery is possible.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Graph Limits Nonparametric Models and Estimation
Sourav Chatterjee