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Wednesday, August 10 • 4:00pm - 5:00pm
Musings on Exabyte Scale Principal Component Analysis

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Modern mathematical algorithms, when wed with high performance computing resources, allow one to treat large scale problems in Data Science.  In particular, dimensionality reduction is one of the cornerstones of data analytics, and such ideas form the foundation for many other approaches commonly used in industry and academics.  In this talk, we will describe how techniques such as low-rank matrix completion can be used to reduce the dimensionality of large scale data sets in an efficient and distributed fashion.  


Wednesday August 10, 2016 4:00pm - 5:00pm PDT
Cherokee Ballroom