Neural Machine Learning I

COMP / ELEC / STAT 502, spring 2014


Class meets: TTH 2:30 - 3:45pm, DCH 1075
Instructor: Erzsébet Merényi
email: erzsebet@rice.edu
Office/Phone: DH 2040, 713-348-3595 
Office hour: Tue 4-5pm, or by appointment
Assistant: Sergii Babkin
Advising: TBA, or by appointment
Assistant: Patrick O'Driscoll
Advising: TBA, or by appointment

Syllabus
Prerequisites
Course Flyer
Disability Allowances

Last Updated: May 5, 2014


End-of-Semester Pizza Awards
Acronyms


Welcome to biologically inspired neural information processing!
Short course description: Review of major Artificial Neural Network paradigms. Analytical discussion of supervised and unsupervised learning. Emphasis on state-of-the-art Hebbian (biologically most plausible) learning paradigms and their relation to information theoretical methods. Applications to data analysis such as pattern recognition, clustering (information discovery), classification, non-linear PCA, independent component analysis, with lots of examples from image and signal processing and other areas. 

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