Neural Machine Learning and Data Mining II

COMP / ELEC / STAT 602, fall 2015



Instructor: Erzsébet Merényi
Class meets: TTH 1:00 - 2:20pm, KCK 107
Office/Phone: DH 2040, 713-348-3595 
Office hours: by appointment
Assistant: N/A
email: erzsebet@rice.edu
Sample Course Topics
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Last Updated: August 24, 2015




Welcome to biologically inspired neural information processing!

Short course description: Advanced topics in ANN theories, with a focus on learning high-dimensional manifolds with neural maps (Self-Organizing Maps and variants, Learning Vector Quantization, both unsupervised and supervised paradigms) (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 research software environment to do simulations.  

Want a small glimpse in layman's terms?