Negative Dependence and Sampling in Machine Learning

Neyman Seminar
Sep 27, 2017 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
Discrete Probability distributions with strong negative dependencies (negative association) occur in a wide range of settings in Machine Learning, from probabilistic modeling to randomized algorithms for accelerating a variety of popular ML models. In addition, these distributions enjoy rich theoretical connections and properties. A prominent example are Determinantal Point Processes. In this...
Stefanie Jegelka, Massachusetts Institute of Technology