This course is an advanced course that follows the basic Machine Learning methods, in particular along the line of supervised approaches. Advanced and new machine learning methods were discussed and studied. We went through some popular topics in machine learning covering:
(1) Multi-class and multi-label classification, (2) Structural prediction (Structural SVM, Conditional random fields), (3) Hidden Markov models, (4) Recurrent neural networks, (5) Semi-supervised learning and weakly-supervised learning, (6) Compressed sensing, sparsity and low-rank, (7) Self-supervised learning, (8) Generative AI