YoVDO

Neural Nets for NLP 2021 - Adversarial Methods

Offered By: Graham Neubig via YouTube

Tags

Neural Networks Courses Natural Language Processing (NLP) Courses Generative Models Courses Adversarial Attacks Courses

Course Description

Overview

Explore adversarial methods in neural networks for natural language processing in this lecture from CMU's CS 11-747 course. Delve into generative adversarial networks, adversarial feature learning, and adversarial attacks and training. Learn about generative models, distribution matching, GANs for text, domain-invariant representations, multitask learning, and unsupervised machine translation. Discover techniques for adversarial robustness, including adversarial examples and training methods. Gain insights into the challenges and applications of adversarial approaches in NLP tasks.

Syllabus

Adversarial Methods
generative models
nonlatent models
examples
models
training method
distribution matching
pseudocode
gans good
gans for text
latent variables
training
text stabilization
discrimination over soft max
Adversarial feature learning
Domain invariant representations
Language variant representations
Multitask learning
Professor forcing
Unsupervised distribution matching
Unsupervised machine translation
Adversarial robustness
Adversarial example
Adversarial training


Taught by

Graham Neubig

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera
Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn
Statistical Learning with R
Stanford University via edX
Machine Learning 1—Supervised Learning
Brown University via Udacity
Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX