CMU Advanced NLP: Structured Learning Algorithms

Explore structured learning algorithms in this advanced Natural Language Processing lecture from Carnegie Mellon University. Delve into reinforcement learning, minimum risk training, and the structured perceptron. Examine structured max-margin objectives and simple remedies to exposure bias. Learn about globally normalized models, sampling and beam search techniques, and various structured training approaches including hinge loss, cost-augmented hinge loss, and contrastive learning. Gain insights into teacher forcing, self-training, and evaluation metrics for structured prediction tasks in NLP.