Explore the concept of Generative Adversarial Minority Oversampling in this 21-minute lecture from the University of Central Florida. Delve into the intricacies of Generative Adversarial Networks and their application in addressing imbalanced datasets. Learn about the proposed method, including the convex generator, additional discriminator, and least-square loss. Examine experiments and results conducted on higher resolution datasets. Gain insights into related works and engage with thought-provoking questions to deepen your understanding of this advanced machine learning technique.
Overview
Syllabus
Intro
Outline
Introduction
Generative Adversarial Networks
Related Works
Proposed Method
Convex Generator
Additional Discriminator
Least-Square Loss
Experiments and Results
Datasets - higher resolution
Questions?
Taught by
UCF CRCV
Tags
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