Advanced Machine Learning

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			Course Handouts This page will contain information and class notes. Also make sure to check the "papers" page for the weekly readings. Course Information Topic 1, Linear/Gaussian Modeling, PCA Topic 2, Nonlinear Dimension Reduction Topic 3, Maximum Entropy Discrimination Topic 4, Linear Models, Conditional Random Fields Topic 5, Graphical Models and Structured SVMs Topic 6, Kernels and Probabilistic Kernels Topic 7, Feature and Kernel Selection Topic 8, Meta-Learning and Multi-Task SVMs Topic 9, Semi-Supervised Learning Topic 9b, Graph-Based Semi-Supervised Learning Topic 10, Beyond Junction Tree: Loopy Models Topic 11, Clustering Topic 12, Boosting PPT File Homework 1 Homework 2 Project