Columbia Year of Statistical Machine Learning

The Columbia Year of Statistical Machine Learning aims to bring together leading researchers whose work is at the forefront of theoretical, methodological, and applied statistical machine learning.

The Columbia Year of Statistical Machine Learning will consist of bi-weekly seminars, workshops, and tutorial-style lectures, with invited speakers.

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Seminar Schedule

September 2019
13 September
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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Rebecca Willett (University of Chicago)

Title: Neumann Networks for Inverse Problems in Imaging

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27 September
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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October 2019
04 October
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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Dean Foster (Amazon Research)

Title: Falsifiability, calibration and a bit of Reinforcement Learning

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25 October
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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Sanjoy Dasgupta (University of California, San Diego)

Title: A data representation from neuroscience

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November 2019
08 November
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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Jason Lee (Princeton University)

Title: Beyond Linearization in Neural Networks

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22 November
School of Social Work Building, 1255 Amsterdam Ave, Room 903
New York, NY 10027 United States
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Satyen Kale (Google Research, NY)

Title: Logistic Regression: The Importance of Being Improper

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