Stochastic Learning
Lecture slides:
- Stochastic Learning
- Summary
- Introduction
- Expected Risk
- Batch Gradient Descent.
- Stochastic Gradient Descent.
- Stochastic vs. Online
- aStochastic/Online vs. Generalization.
- More General.
- Adaline
- Multilayer network.
- Non Differentiable Loss Functions.
- Rosenblatt´s perceptron.
- K-Means
- aLearning Vector Quantization.
- Stochastic Noise.
- Speed Advantage.
- Many examples:
- Other approaches.
Author: Léon Bottou, Nec Research