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  • CS Colloquium: Arindam Banerjee (University of Minnesota, Twin Cities) - Learning with Low Samples in High-Dimensions: Estimators, Geometry, and Applications

    Thu, Nov 17, 2016 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Arindam Banerjee, University of Minnesota, Twin Cities

    Talk Title: Learning with Low Samples in High-Dimensions: Estimators, Geometry, and Applications

    Series: Yahoo! Labs Machine Learning Seminar Series

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium. Part of Yahoo! Labs Machine Learning Seminar Series.

    Many machine learning problems, especially scientific problems in areas such as ecology, climate science, and brain sciences, operate in the so-called `low samples, high dimensions' regime. Such problems typically have numerous possible predictors or features, but the number of training examples is small, often much smaller than the number of features. In this talk, we will discuss recent advances in general formulations and estimators for such problems. These formulations generalize prior work such as the Lasso and the Dantzig selector. We will discuss the geometry underlying such formulations, and how the geometry helps in establishing finite sample properties of the estimators. We will also discuss applications of such results in structure learning in probabilistic graphical models, along with real world applications in ecology and climate science.

    This is joint work with Soumyadeep Chatterjee, Sheng Chen, Farideh Fazayeli, Andre Goncalves, Jens Kattge, Igor Melnyk, Peter Reich, Franziska Schrodt, Hanhuai Shan, and Vidyashankar Sivakumar.

    Biography: Arindam Banerjee is an Associate Professor at the Department of Computer & Engineering and a Resident Fellow at the Institute on the Environment at the University of Minnesota, Twin Cities. His research interests are in statistical machine learning and data mining, and applications in complex real-world problems including climate science, ecology, recommendation systems, text analysis, brain sciences, finance, and aviation safety. He has won several awards, including the Adobe Research Award (2016), the IBM Faculty Award (2013), the NSF CAREER award (2010), and six Best Paper awards in top-tier conferences.

    Host: Yan Liu

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair


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