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Negative Dependence: Theory and Applications in Machine Learning
Mike Gartrell · Jennifer Gillenwater · Alex Kulesza · Zelda Mariet

Fri Jun 14 08:30 AM -- 06:00 PM (PDT) @ 204
Event URL: https://negative-dependence-in-ml-workshop.lids.mit.edu »

Models of negative dependence are increasingly important in machine learning. Whether selecting training data, finding an optimal experimental design, exploring in reinforcement learning, or making suggestions with recommender systems, selecting high-quality but diverse items has become a core challenge. This workshop aims to bring together researchers who, using theoretical or applied techniques, leverage negative dependence in their work. We will delve into the rich underlying mathematical theory, understand key applications, and discuss the most promising directions for future research.

Author Information

Mike Gartrell (Criteo AI Lab)
Jennifer Gillenwater (Google Research NYC)
Alex Kulesza (Google)
Zelda Mariet (Massachusetts Institute of Technology)

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