Cognitive Systems Talk: Machine Learning in a Snap

Invitation to the ISSIP Cognitive Systems Institute Group Webinar

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Talk Title: Machine Learning in a Snap    August 30, 2018 - 10:30am US Eastern
Speaker: Thomas Parnell, IBM

Talk Description:
Generalized linear models, such as logistic regression and support vector machines, remain some of the most widely-used techniques in the machine learning field. Their enduring popularity can be attributed to their desirable theoretical properties, effective training algorithms, and relative ease of interpretability. In this talk we will introduce Snap Machine Learning: a new library for fast training of such models, that is designed to enable new real-time and large-scale applications. The library was designed from the ground up with performance in mind. It exploits parallelism at three different levels: across multiple machines in a network, across heterogeneous compute nodes within a machine (e.g. CPU and GPU), as well as the massive parallelism offered by modern GPUs. In this talk we will review this new architecture and give examples of how the library can be used via the various APIs that are provided (e.g. Python, Apache Spark, MPI). Finally, we will present benchmarking results using the publicly available Terabyte Click Logs dataset (from Criteo Labs) and show that Snap Machine Learning can train a logistic regression classifier in 1.53 minutes, 46x faster than any of the results that have been previously reported using the same dataset.

Bio: 
Thomas received his B.Sc. and Ph.D. degrees in mathematics from the University of Warwick. U.K., in 2006 and 2011, respectively. He joined Arithmatica, Warwick, U.K., in 2005, where he was involved in FPGA design and electronic design automation. In 2007, he co-founded Siglead Europe, a U.K.-limited subsidiary of Yokohama-based Siglead Inc., where he was involved in developing signal processing and error-correction algorithms for HDD, flash, and emerging storage technologies. In 2013, he joined IBM Research in Zürich, Switzerland, where he is actively involved in the research and development of machine learning, compression and error-correction algorithms for IBM’s storage and AI products. His research interests include signal processing, information theory, machine learning and recommender systems.

Date and Time : August 30 2018 - 10:30am US Eastern
Zoom meeting Link: https://zoom.us/j/7371462221
Zoom Callin: (415) 762-9988 or (646) 568-7788 Meeting id 7371462221
Zoom International Numbers: https://zoom.us/zoomconference
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