Copyright 2003 AACS Idaho State University E. S. Lohse, PhD [email protected] C. Schou, PhD [email protected] D. Sammons, EdD [email protected] R. Schlader,
Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle NIPS 2007 Presented by Ahmed Hefny.
Analysis of Classification Algorithms in Handwriting Pattern Recognition Logan Helms Jon Daniele.
Techniques for the analysis of GM structure: VBM, DBM, cortical thickness Jason Lerch.
Supervised learning 1.Early learning algorithms 2.First order gradient methods 3.Second order gradient methods.
1 Chapter 11 Neural Networks. 2 Chapter 11 Contents (1) l Biological Neurons l Artificial Neurons l Perceptrons l Multilayer Neural Networks l Backpropagation.
Supervised Learning: Perceptrons and Backpropagation.
