Chapter: 9: Gradient Descent Algorithms

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Home > An Introduction to Neural Networks > 9: Gradient Descent Algorithms

An Introduction to Neural Networks |

James A. Anderson

MIT Press,

9: Gradient Descent Algorithms

Chapter Info

ARI Id

1671269581176_11298

Access

Not Available Free

DOI

10.7551/mitpress/3905.003.0011

Chapter URL

https://direct.mit.edu/books/book/3986/chapter/166245/Gradient-Descent-Algorithms

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Chapters/Headings	Author(s)	Pages	Info
1: Properties of Single Neurons
2: Synaptic Integration and Neuron Models
3: Essential Vector Operations
4: Lateral Inhibition and Sensory Processing
5: Simple Matrix Operations
6: The Linear Associator: Background and Foundations
7: The Linear Associator: Simulations
8: Early Network Models
9: Gradient Descent Algorithms
10: Representation of Information
11: Applications of Simple Associators
12: Energy and Neural Networks
13: Nearest Neighbor Classifiers
14: Adaptive Maps
15: The BSB Model
16: Associative Computation
17: Teaching Arithmetic to a Neural Network
Afterword
Index
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