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Advanced NLP: Adversarial Methods for Text

Graham Neubig via YouTube

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This lecture examines how adversarial methods can be applied to text, covering GANs, discriminators, training stabilization, feature learning, and discrete inputs and outputs. It also discusses applications including multitask learning, unsupervised style transfer, and unsupervised alignment.

Syllabus

Introduction
Adversarial Methods
generative adversarial networks
No generative models
Basic Paradigm
Training Method
Distribution Matching
Pseudocode
Why
Problems
Applications
Learning Methods
Discriminators
Comparing two outputs
Training a discriminator
Stabilization tricks
Discriminator over results
Adversarial Feature Learning
MultiTask Learning
Professor Forced
Unsupervised Style Transfer
Unsupervised Alignment

Taught by

Graham Neubig

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