Credits: 3 (3-0-0)
Description
Advanced topics in machine learning, including Nonlinear Dimension Reduction, Maximum Entropy, Exponential Family Models, Graphical Models; Computational Learning Theory, Structured Support Vector Machines, Feature Selection, Kernel Selection, Meta-Learning, Multi- Task Learning, Semi-Supervised Learning, Reinforcement Learning, Approximate Inference, Clustering, and Boosting.