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Algorithmic Learning Theory

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Cover of 'Algorithmic Learning Theory'

Table of Contents

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    Book Overview
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    Chapter 29 Managing complexity in neuroidal circuits
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    Chapter 30 Learnability of exclusive-or expansion based on monotone DNF formulas
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    Chapter 31 Improved bounds about on-line learning of smooth functions of a single variable
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    Chapter 32 Query learning of bounded-width OBDDs
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    Chapter 33 Learning a representation for optimizable formulas
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    Chapter 34 Limits of exact algorithms for inference of minimum size finite state machines
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    Chapter 35 Genetic fitness optimization using rapidly mixing Markov chains
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    Chapter 36 The kindest cut: Minimum message length segmentation
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    Chapter 37 Reducing complexity of decision trees with two variable tests
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    Chapter 38 The complexity of exactly learning algebraic concepts
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    Chapter 39 Efficient learning of real time two-counter automata
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    Chapter 40 Cost-sensitive feature reduction applied to a hybrid genetic algorithm
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    Chapter 41 Effects of Feature Selection with ‘Blurring’ on neurofuzzy systems
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    Chapter 42 Boosting first-order learning
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    Chapter 43 Incorporating hypothetical knowledge into the process of inductive synthesis
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    Chapter 44 Induction of Constraint Logic Programs
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    Chapter 45 Constructive learning of translations based on dictionaries
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    Chapter 46 Inductive logic programming beyond logical implication
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    Chapter 47 Noise elimination in inductive concept learning: A case study in medical diagnosis
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    Chapter 48 MML estimation of the parameters of the spherical fisher distribution
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    Chapter 49 Learning by erasing
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    Chapter 50 On learning and co-learning of minimal programs
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    Chapter 51 Inductive inference of unbounded unions of pattern languages from positive data
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    Chapter 52 A class of prolog programs inferable from positive data
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    Chapter 53 Vacillatory and BC learning on noisy data
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    Chapter 54 Transformations that preserve learnability
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    Chapter 55 Probabilistic limit identification up to “small” sets
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    Chapter 56 Reflecting inductive inference machines and its improvement by therapy
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Title
Algorithmic Learning Theory
Published by
Springer Berlin Heidelberg, January 2006
DOI 10.1007/3-540-61863-5
ISBNs
978-3-54-061863-8, 978-3-54-070719-6
Editors

Arikawa, Setsuo, Sharma, Arun K.