• Academy Events

  • 8th Annual Machine Learning Symposium

    Friday, March 28, 2014 | 9:00 AM - 5:00 PM
    The New York Academy of Sciences

    Presented by the Machine Learning Discussion Group at the New York Academy of Sciences

    In our current digital age, a wealth of data is available at our fingertips. Often, the value of this 'Big Data' is not in the data itself, but the ability to learn from historical data in order to make predictions. Machine Learning, a branch of artificial intelligence, 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 function, medical diagnosis, credit card fraud detection, and stock market analysis.

    This symposium — part of 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. Speakers include Rayid Ghani (University of Chicago), former Chief Data Scientist for the Obama for America 2012 re-election campaign; IBM specialist in automatic speech recognition, Brian Kingsbury; and Northwestern University's Jorge Nocedal, who shall discuss the role of machine learning in optimization.

    2014 Spotlight Talk Awards

    The New York Academy of Sciences congratulates the winners of the 2014 Spotlight Talk Awards, which recognized a series of the best oral research presentations delivered by early career investigators during the Symposium.

    Generative Image Models for Visual Phenotype Modeling
    Theofanis Karaletsos
    Memorial Sloan-Kettering Cancer Center

    Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction
    Jennifer Gillenwater, BS
    University of Pennsylvania

    Learning from Label Proportions: Algorithm, Theory, and Application
    Felix X. Yu, MSc
    Columbia University

    Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch
    Partha Pratim Talukdar, PhD
    Carnegie Mellon University

    Accelerated Parallel Optimization Methods for Large Scale Machine Learning
    Haipeng Luo, PhD candidate
    Princeton University

    Learning Theory and Algorithms for Revenue Optimization in Second-Price Auctions with Reserve
    Andrés Muñoz Medina
    Courant Institute of Mathematical Sciences, New York University

    Google is the proud sponsor of the Spotlight Talk awards.

    Registration Pricing

    Member $30
    Student / Postdoc Member $15
    Nonmember (Academia) $65
    Nonmember (Corporate) $85
    Nonmember (Non-profit) $65
    Nonmember (Student / Postdoc / Resident / Fellow) $45