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Handbook on Neural Information Processing

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Cover of 'Handbook on Neural Information Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Deep Learning of Representations
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    Chapter 2 Recurrent Neural Networks
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    Chapter 3 Supervised Neural Network Models for Processing Graphs
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    Chapter 4 Topics on Cellular Neural Networks
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    Chapter 5 Approximating Multivariable Functions by Feedforward Neural Nets
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    Chapter 6 Bochner Integrals and Neural Networks
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    Chapter 7 Semi-supervised Learning
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    Chapter 8 Statistical Relational Learning
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    Chapter 9 Kernel Methods for Structured Data
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    Chapter 10 Multiple Classifier Systems: Theory, Applications and Tools
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    Chapter 11 Self Organisation and Modal Learning: Algorithms and Applications
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    Chapter 12 Bayesian Networks, Introduction and Practical Applications
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    Chapter 13 Relevance Feedback in Content-Based Image Retrieval: A Survey
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    Chapter 14 Learning Structural Representations of Text Documents in Large Document Collections
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    Chapter 15 Neural Networks in Bioinformatics
Attention for Chapter 5: Approximating Multivariable Functions by Feedforward Neural Nets
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