Explore advanced methods for text classification and sequence labeling in this 50-minute video lecture from CMU's Multilingual Natural Language Processing course. Delve into subword models, unsupervised training, and structured prediction models. Learn about bi-directional RNNs, bag of n-grams, and solutions for unknown words. Discover subword segmentation algorithms and embedding models, including cross-lingual learning techniques. Examine strategies for handling limited labeled data, such as joint multi-task learning and pre-training with masked language modeling. Compare multilingual representations and understand the importance of structured prediction in NLP tasks. Gain insights into local vs. global normalization and potential functions in advanced text classification and labeling techniques.