58 min
New Directions in Property Testing | Richard M. Karp Distinguished Lecture
Computer Science, Data Science, Machine Learning and seminar by Rocco Servedio, Columbia University
Hosted by Simons Institute for the Theory of Computing, UC Berkeley
Wednesday 15:30 Los Angeles (GMT-7)
Recording available
Berkeley, United States
Recording
Abstract
Rocco Servedio surveys algorithms that determine whether very large objects possess a property, or are far from having it, by examining only a small part. The lecture covers progress on classic problems and newer testing frameworks motivated by machine-learning theory and high-dimensional data analysis.
Topics
large objectsclassic problemstesting frameworksmachine-learning theoryhigh-dimensional data analysis
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