Large Scale Machine Learning with the SimSQL System

Friday, March 07, 2014
ENS 637

Join Professor Christopher Jermaine from Rice University for a talk that describes the SimSQL System, a platform for writing and executing machine-learning codes. Since SimSQL is at its heart a relational database system, it is designed to support data independence. That is, the same declarative statistical inference codes can be used regardless of data set size, computer 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. Professor Jermaine has participated in extensive experimentation and found that SimSQL performs as well as other competitive platforms that support writing and exeucting machine-learning codes for large data sets.


Associate Professor of Computer Science
Rice University

Christopher 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. Professor Jermaine received a BA in Mathematics from University of California - San Diego, an MSc in Computer Science and Engineering from Ohio State University and a PhD from the College of Computing at Georgia Tech University.