Advanced Machine Learning & Perception
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Advanced Machine Learning & Perception
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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. Please do not distribute the book files, limited access has been given to us by the authors, please respect their wishes. Course Information Text Book: FILES ON COURSEWORKS Topic 1, Linear/Gaussian Modeling, PCA Topic 2, Nonlinear Dimension Reduction Topic 3, SVMs and Large (Relative) Margin Topic 4, SVM Feature and Kernel Selection Topic 5, Maximum Entropy Discrimination Topic 6, MultiTask SVMs Topic 7, Kernels and Probabilistic Kernels Topic 8, Multi-Class & Structured Prediction Topic 9, Structured MAP Decoding & Graphical Models Topic 9+, MAP Estimation and Loopy Message Passing Homework 1 Homework 2 (Available Oct. 30, broken link, sorry!) Project Information | ||||||||
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