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Cryptographic Limitations on Learning Boolean Formulae and Finite Automata

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Cover of 'Cryptographic Limitations on Learning Boolean Formulae and Finite Automata'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 18 Strategic directions in machine learning
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    Chapter 19 Introduction
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    Chapter 20 Training a 3-node neural network is NP-complete
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    Chapter 21 Cryptographic limitations on learning Boolean formulae and finite automata
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    Chapter 22 Inference of finite automata using homing sequences
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    Chapter 23 Introduction
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    Chapter 24 Adaptive search by learning from incomplete explanations of failures
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    Chapter 25 Learning of rules for fault diagnosis in power supply networks
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    Chapter 26 Cross references are features
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    Chapter 27 The schema mechanism
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    Chapter 28 L-ATMS: A tight integration of EBL and the ATMS
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    Chapter 29 Introduction
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    Chapter 30 Massively parallel symbolic induction of protein structure/function relationships
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    Chapter 31 Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks
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    Chapter 32 Phoneme discrimination using connectionist networks
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    Chapter 33 Behavior-based learning to control IR oven heating: Preliminary investigations
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    Chapter 34 Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks
Attention for Chapter 23: Introduction
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Chapter title
Introduction
Chapter number 23
Book title
Machine Learning: From Theory to Applications
Published by
Springer, Berlin, Heidelberg, January 1993
DOI 10.1007/3-540-56483-7_23
Book ISBNs
978-3-54-056483-6, 978-3-54-047568-2
Authors

Werner Remmele, Remmele, Werner

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