HMC CS 152 Lecture Slides, Fall 2004

Date	Topic	pdf file
8/31	Introduction and Perceptrons	introPerceptrons
9/02	Learning	learning
9/07	Adalines	Adalines
9/09	Vector Calculus Topics
9/16	Adaptive Filters	Adaptive Filters
9/21	Backpropagation	Backpropagation
9/23	Backpropagation applications	Backpropagation Application
9/23	Backpropagation tips and tricks	Backpropagation tips and tricks
9/28	Backpropagation variations	Backpropagation variations
9/30	Time in Neural Networks	Time
10/05	Real-Time Recurrent Learning Derivation
10/07	Temporal Difference Method	Temporal differences
10/12	Radial Basis Function Networks	RBF's
10/12	Support Vector Machines	SVM's
10/14	Supervised Hebbian Learning	Hebb
10/14	Unsupervised Hebbian Learning	Assoc
10/26	Competitive Learning	Compet
10/28	Self-Organizing Maps	SOM
11/02	Principal Components Analysis	PCA
11/04	Wan and Beuafays Paper Review	wanbeaufays
11/04	Hopfield Nets	Hopfield
11/16	Boltzmann Machines	Boltzmann
11/16	Adaptive Resonance Theory	ART
11/23	Vanishing Gradient in Recurrent Neural Models	Presentation by Garret Heckel
11/23	Growing Neural Gas	Presentation by Jonathan Beall
11/30	Fuzzy Logic	Fuzzy