Overview
Syllabus
Intro
Generative Models
Adversarial Training
Basic Paradigm
Problems with Generation • Over-emphasis of common outputs, fuzziness Adversarial
Training Method
In Equations
Problems w/ Training
Applications of GAN Objectives to Language
Problem! Can't Backprop through Sampling
Solution: Use Learning Methods for Latent Variables
Discriminators for Sequences
Stabilization Trick
Interesting Application: GAN for Data Cleaning (Yang et al. 2017)
Adversaries over Features vs. Over Outputs
Learning Domain-invariant Representations (Ganin et al. 2016) • Learn features that cannot be distinguished by domain
Adversarial Multi-task Learning (Liu et al. 2017)
Implicit Discourse Connection Classification w/ Adversarial Objective
Professor Forcing (Lamb et al. 2016)
Unsupervised Style Transfer for Text (Shen et al. 2017)
Taught by
Graham Neubig