Machine Learning, a subfield of computer science, involves the development of mathematical algorithms that discover knowledge from specific data sets, and then "learn" from the data in an iterative fashion that allows predictions to be made. Today, Machine Learning has a wide range of applications, including natural language processing, search engine optimization, medical diagnosis and treatment, financial fraud detection, and stock market analysis.
This symposium, the eleventh in an ongoing series presented by the Machine Learning Discussion Group at the New York Academy of Sciences, will feature Keynote Presentations from leading scientists in both applied and theoretical Machine Learning and Spotlight Talks, a series of short, early career investigator presentations across a variety of topics at the frontier of Machine Learning.
Registration for this event will be required. Early registration is strongly encouraged as the 2016 Symposium sold out well in advance.
Call for Abstracts — Deadline January 13, 2017
Abstract submissions are invited for consideration for ten short "Spotlight Talks" as well as presentation in a poster session. For complete submission instructions, please send an email to firstname.lastname@example.org with the words "Abstract Information" in the subject line.
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