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When Do Dependencies in Your Data Help? - Emerging Generalization Settings

Offered By: Simons Institute via YouTube

Tags

Machine Learning Courses Computational Complexity Courses Markov Chain Monte Carlo Courses Probabilistic Inference Courses

Course Description

Overview

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Explore a 59-minute lecture by Ankur Moitra from the Massachusetts Institute of Technology, presented at the Simons Institute, on the topic of "When do dependencies in your data help?" Delve into the problem of learning graphical models from iid data and discover how assuming data generation through the Glauber dynamics process can overcome computational barriers by leveraging dependencies. Gain insights into emerging generalization settings and understand the collaborative research findings of Jason Gaitonde and Elchanan Mossel in this informative talk on computational learning theory and data dependencies.

Syllabus

When do dependencies in your data help?


Taught by

Simons Institute

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