Towards Robustness Against Natural Language Adversarial Attacks
Offered By: VinAI via YouTube
Course Description
Overview
Explore the challenges and solutions in defending against natural language adversarial attacks in this seminar by VinAI researcher Luu Anh Tuan. Delve into various types of natural language attacks and their impact on deep neural networks in NLP systems. Examine recent defense strategies and their limitations. Learn about the innovative Adversarial Sparse Convex Combination (ASCC) method, which models the attack space as a convex hull and aligns better with discrete textual space. Discover how ASCC-defense generates worst-case perturbations and incorporates adversarial training to enhance robustness. Gain insights into a new class of defense techniques for NLP, including the potential of robustly trained word vectors to improve model resilience without additional defense measures.
Syllabus
Seminar Series: Towards Robustness Against Natural Language Adversarial Attacks
Taught by
VinAI
Related Courses
Applied Text Mining in PythonUniversity of Michigan via Coursera Natural Language Processing
Higher School of Economics via Coursera Exploitez des données textuelles
CentraleSupélec via OpenClassrooms Basic Sentiment Analysis with TensorFlow
Coursera Project Network via Coursera Build Multilayer Perceptron Models with Keras
Coursera Project Network via Coursera