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 Topic 4, Linear Models, Conditional Random Fields Topic 5, Graphical Models and Structured SVMs Topic 6, Beyond Junction Tree: High Tree-Width Models Topic 7, Kernels and Probabilistic Kernels Topic 8, Feature and Kernel Selection Topic 9, Meta-Learning and Multi-Task SVMs Topic 10a, Semi-Supervised Learning Topic 10b, Graph-Based Semi-Supervised Learning Topic 11, Clustering Topic 11b, Clustering (Proof) Topic 12, Boosting PPT File Homework 1 Homework 2 Project