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Theory of GANs for Compressed Sensing

Offered By: Paul Hand via YouTube

Tags

Generative Adversarial Networks (GAN) Courses Artificial Intelligence Courses Machine Learning Courses Optimization Problems Courses Compressed Sensing Courses

Course Description

Overview

Explore the theory of Generative Adversarial Networks (GANs) for compressed sensing in this 57-minute lecture from Northeastern University's CS 7180 Spring 2020 class on Special Topics in Artificial Intelligence. Delve into topics such as visual representation, set restricted eigen value condition, and optimization problems related to GANs in compressed sensing. Examine the Gaussian model, key claims, and commentary on the subject. Access accompanying lecture notes and referenced papers to deepen understanding of this advanced artificial intelligence topic.

Syllabus

Introduction
Visual Representation
Set Restricted Eigen Value Condition
Proof
Dilemma
Structure
Optimization Problem
Gaussian Model
Claim
Commentary


Taught by

Paul Hand

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