Large Scale Machine Learning with the SimSQL System
Associate Professor of Computer Science
Tuesday, February 04, 2014|
4:00pm - 5:30pm
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About the Event
In this talk, I'll describe the SimSQL system, which is a platform for writing and executing machine learning codes. Since SimSQL is at its heart a relational database system, it designed to support data independence. That is, the same declarative statistical inference codes can be used regardless of data set size, compute hardware, and physical data storage and distribution across machines. One concern is that a platform supporting data independence in this way will not perform well. But we've done extensive experimentation, and have found that SimSQL performs as well as other competitive platforms that support writing and executing machine learning codes for large data sets.
Chris Jermaine is an associate professor of computer science at Rice University. He is the recipient of an Alfred P. Sloan Foundation Research Fellowship, a National Science Foundation CAREER award, and an ACM SIGMOD Best Paper Award. In his spare time, Chris enjoys outdoor activities such as hiking, climbing, and whitewater boating. In one particular exploit, Chris and his wife floated a whitewater raft (home-made from scratch using a sewing machine, glue, and plastic) over 100 miles down the Nizina River (and beyond) in Alaska.
Contact: Stephen Reger
Open to: Public