ELEC 602 / COMP 602, fall 2012
Short course description: Advanced topics in ANN theories, with a focus on learning high-dimensional manifolds with self-organized learning, Self-Organizing Maps and variants, (unsupervised learning in general). Application to clustering, classification, dimension reduction, sparse representation. Comparison with "gold standards" through examples from image and signal processing. The course will be a mix of lectures and seminar style discussions with active student participation, based on recent research publications. Students will have access to professional software environment to implement theories.
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