Advanced topics in machine learning including: Linear Modeling, Nonlinear Dimension Reduction, Maximum Entropy, Exponential Family Models, Conditional Random Fields, Graphical Models, Structured Support Vector Machines, Feature Selection, Kernel Selection, Meta-Learning, Multi-Task Learning, Semi-Supervised Learning, Graph-Based Semi-Supervised Learning, Approximate Inference, Clustering, and Boosting. .
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