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. Handout 1: Course Information Handout 2: Text Book: FILES ON COURSEWORKS Handout 3: Topic 1, Linear/Gaussian Modeling, PCA Handout 4: Topic 2, Nonlinear Dimension Reduction Handout 5: Topic 3, SVMs and Large (Relative) Margin Handout 6: Topic 4, SVM Feature and Kernel Selection Handout 7: Topic 5, Maximum Entropy Discrimination Handout 8: Topic 6, MultiTask SVMs Homework 1 Homework 2 (Available Oct. 30, broken link, sorry!) Project Information | |||||||||
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