In this video I explain the "Adversarial Discriminative Domain Adaptation" (or ADDA for short) paper by University of California Berkley, Stanford University and Boston University. This is a algorithm that helps in solving the domain shift problem when training deep neural networks.
*Related Videos*
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In the paper explained series "Wav2Vec2": https://youtu.be/fMqYul2TvBE
*References*
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Adversarial Discriminative Domain Adaptation paper: https://arxiv.org/abs/1702.05464
*Contents*
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00:00 - Intro
00:22 - Domain Adaptation Intro
02:04 - Abstract
03:15 - Algorithm Overview
05:14 - Other Domain Adaptation Algorithms
05:42 - Generalized Adversarial Adaptation
07:49 - Feature Mappings
08:54 - Adversarial Losses
10:15 - ADDA Algorithm
12:08 - Evaluation & Results
14:07 - Outro
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