Previously, the Department of Statistics together with the TRIPODS Institute, held numerous activities on statistical machine learning, comprising a Special Year of Statistical ML (2019-2020).
Rebecca Willett (University of Chicago), on Neumann Networks for Inverse Problems in Imaging
Peter Bartlett (University of California, Berkeley), on Benign Overfitting
Dean Foster (Amazon Research), on Falsifiability, calibration and a bit of Reinforcement Learning
Sanjoy Dasgupta (University of California, San Diego), on A data representation from neuroscience
Jason Lee (Princeton University), on Beyond Linearization in Neural Networks
Satyen Kale (Google Research), on Logistic Regression: The Importance of Being Improper
Rebecca Willett (University of Chicago)
Title: Neumann Networks for Inverse Problems in Imaging
New York, NY 10027 United States
Peter Bartlett (University of California, Berkeley)
Title: Benign Overfitting
New York, NY 10027 United States
Dean Foster (Amazon Research)
Title: Falsifiability, calibration and a bit of Reinforcement Learning
New York, NY 10027 United States
Sanjoy Dasgupta (University of California, San Diego)
Title: A data representation from neuroscience
New York, NY 10027 United States
Jason Lee (Princeton University)
Title: Beyond Linearization in Neural Networks
New York, NY 10027 United States
Satyen Kale (Google Research, NY)
Title: Logistic Regression: The Importance of Being Improper
New York, NY 10027 United States
Tutorials on Sampling and Variational Inference
Speakers: Max Raginsky, Tamara Broderick, Dave Blei
