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  • Machine Learning Discussion Group

    Machine learning, the study of computer algorithms that improve automatically through experience, has a wide spectrum of applications, including natural language processing, search engines, medical diagnosis, bioinformatics and cheminformatics, detecting credit card fraud, and stock market analysis.

    The Machine Learning Discussion Group holds an annual symposium each fall to discuss advanced research related to such topics. Participants come from a variety of disciplines and from both academic and industry institutions, promoting the exchange of new insights between communities.

  • Events

    Friday, March 3, 2017 | 9:00 AM - 6:30 PM

    11th Annual Machine Learning Symposium

    Keynote Speakers: Kamalika Chaudhuri (University of California San Diego), Tim Roughgarden (Stanford University), and Suchi Saria (Johns Hopkins University)

    The 11th Annual Machine Learning Symposium is the latest in a highly successful series bringing together leading researchers from academia and industry to present new algorithms for statistical learning and novel theoretical approaches and discuss applications of ML to real-world data. In addition, the workshop will address limitations of existing techniques and solutions to overcome such shortcomings.

  • Past Events

    Friday, March 4, 2016 | 9:00 AM - 6:00 PM

    10th Annual Machine Learning Symposium

    Keynote Speakers: Sébastien Bubeck (Microsoft Research), Alex Graves (Google Research), Alexander Rakhlin (University of Pennsylvania), Ambuj Tewari (University of Michigan)

    This symposium features keynote speakers in applied and theoretical machine learning as well as "spotlight" talks selected from poster abstract submissions.

    Friday, March 13, 2015 | 9:00 AM - 5:00 PM

    9th Annual Machine Learning Symposium

    Keynote Speakers: Pedro Domingos (University of Washington), Yoshua Bengio (Université de Montréal), Elad Hazan (Princeton University)

    This symposium featured keynote presentations from leading scientists in both applied and theoretical Machine Learning and research presentations delivered by early career investigators.

    Friday, March 28, 2014 | 9:00 AM - 5:00 PM

    8th Annual Machine Learning Symposium

    Keynote Speakers: Rayid Ghani (University of Chicago), Brian Kingsbury (IBM), Jorge Nocedal (Northwestern University)

    Chief Data Scientist for the 'Obama for America' 2012 re-election campaign, and other experts, explore the latest innovations in harnessing the power of big data through machine learning.

    Friday, October 19, 2012 | 9:30 AM - 5:00 PM

    7th Annual Machine Learning Symposium

    Peter Bartlett (University of California, Berkeley), William Freeman (Massachusetts Institute of Technology) and Vladimir Vapnik (Columbia University and NEC-labs)

    This symposium features keynote speakers in applied and theoretical machine learning as well as "spotlight" talks selected from poster abstract submissions.

    Friday, October 21, 2011 | 9:30 AM - 5:15 PM

    6th Annual Machine Learning Symposium

    Speakers: Stephen P. Boyd (Stanford University), Leon Bottou (Microsoft adCenter)and Yoav Freund, (University of California)

    The Machine Learning Symposium series aims to build a community of scientists in machine learning from the NYC area's academic, government, and industrial institutions.

    Friday, October 22, 2010 | 9:30 AM - 5:00 PM

    5th Annual Machine Learning Symposium

    Speakers: David Blei (Princeton University), Sanjoy Dasgupta (University of California, San Diego), Michael Collins (Massachusetts Institute of Technology), and Yann LeCun (New York University)

    The aim of these series of symposia is to build a community of scientists in machine learning from the NYC area's academic, government, and industrial institutions by convening and promoting the exchange of ideas in a neutral setting.

    Friday, November 6, 2009 | 10:00 AM - 4:30 PM

    4th Annual Machine Learning Symposium

    Speakers: Robert Bell (AT&T Labs Research), Avrim Blum (Carnegie Mellon University), Thorsten Joachims (Cornell University), Philip Long (Google)

    The aim of the annual Machine Learning Symposium is to build a community of scientists in machine learning from the NYC area's academic, government, and industrial institutions by convening and promoting the exchange of ideas in a neutral setting.

    Friday, October 10, 2008 | 10:00 AM - 4:30 PM

    3rd Annual Machine Learning Symposium

    This is the third symposium on Machine Learning at the New York Academy of Sciences. These series of symposia aim to build a community of scientists in all areas of machine learning in academic, government, and industrial institutions by convening and promoting the exchange of ideas in a collegial setting.

    Friday, October 12, 2007 | 10:00 AM - 4:00 PM

    2nd Annual Machine Learning Symposium

    Speakers: Leslie Pack Kaelbling (MIT), Yishay Mansour (Google and Tel-Aviv University), Fernando Pereira (University of Pennsylvania), and Michael L. Littman (Rutgers University)

    The primary goal of this symposium is to build a community of scientists in machine learning by convening and promoting the exchange of ideas in a neutral setting.

    Friday, October 27, 2006 | 10:00 AM - 4:00 PM

    Machine Learning Symposium

    The primary goal of this symposium is to build a community of scientists in machine learning by convening and promoting the exchange of ideas in a neutral setting.

  • Steering Committee

    Naoki Abe, PhD

    IBM Research

    Corinna Cortes, PhD

    Google

    Jennifer L. Costley, PhD

    The New York Academy of Sciences

    Patrick Haffner, PhD

    AT&T Labs Research

    Tony Jebara, PhD

    Columbia University

    John Langford, PhD

    Microsoft Research

    Mehryar Mohri, PhD

    Courant Institute of Mathematical Sciences

    Gunnar Rätsch, PhD

    Memorial Sloan-Kettering Cancer Center

    Robert Schapire, PhD

    Microsoft Research

    Di Xu, PhD

    American Express


  • Sponsors

    • American Express
    • IBM

    Mission Partner support for the Frontiers of Science program provided by:

    • Johnson & Johnson

    Get more information about how you can sponsor a discussion group.

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