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Cookbook Lower Bounds for Statistical Inference in Distributed and Constrained Settings - Part 1

Offered By: IEEE via YouTube

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IEEE FOCS: Foundations of Computer Science Courses Statistical Inference Courses

Course Description

Overview

Explore fundamental concepts in distributed learning and statistical inference through this IEEE conference talk. Delve into protocols, models, and general formulations for distributed settings. Examine two sets of distributions, focusing on discrete distributions and those over high-dimensional domains. Gain insights into the challenges and approaches in constrained statistical inference, with references provided for further study.

Syllabus

Introduction
Distributed Learning and Testing
Example
Model
Protocols
Models
General formulation
Two sets of distributions
Discrete distributions
Distribution over a highdimensional domain
Discrete distribution
References
Outline


Taught by

IEEE FOCS: Foundations of Computer Science

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