Machine Learning Summer School 2003 - Tuebingen

Stochastic Learning

author: Léon Bottou, NEC Research

Categories

Top: Computer Science: Machine Learning: Statistical Learning
Top: Computer Science: Machine Learning: Neural Networks

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*Slides*
0:01	Stochastic Learning
1:42	Summary
3:07	Introduction
3:37	Expected Risk
4:34	Batch Gradient Descent.
5:24	Stochastic Gradient Descent.
5:59	Stochastic vs. Online
6:50	aStochastic/Online vs. Generalization.
7:56	More General.
8:30	Adaline
10:19	Multilayer network.
11:57	Multilayer network.
12:05	Non Differentiable Loss Functions.
13:20	Rosenblatt´s perceptron.
14:18	K-Means
15:02	aLearning Vector Quantization.
16:43	Stochastic Noise.
18:39	Speed Advantage.
19:46	Many examples:
21:09	Other approaches.

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