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Activity Number: 306 - Algorithmic and Inferential Advances in Univariate and Multivariate Tuning-Parameter-Free Nonparametric Procedures
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #314106
Title: Learning Multivariate Log-Concave Densities
Author(s): Ilias Diakonikolas*
Companies: UW Madison

We will survey recent work from the computer science community on the problem of estimating multivariate log-concave densities. Specifically, we will give an overview of the following contributions: (1) We will describe an estimator that yielded the first known finite sample upper bound for the problem. (2) We will sketch an analysis that gave the first finite sample complexity bound for the multivariate log-concave MLE in d>3 dimensions. (3) We will describe the first algorithm to compute the multivariate log-concave MLE in sample polynomial time.

Authors who are presenting talks have a * after their name.

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