Algorithmic Learning Theory

Table of Contents

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   Book Overview
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   Chapter 31 Program error detection/correction: Turning PAC learning into Perfect learning
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   Chapter 32 Team learning as a game
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   Chapter 33 Inferability of recursive real-valued functions
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   Chapter 34 Learning of R.E. Languages from good examples
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   Chapter 35 Identifiability of subspaces and homomorphic images of zero-reversible languages
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   Chapter 36 On exploiting knowledge and concept use in learning theory
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   Chapter 37 Partial occam's razor and its applications
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   Chapter 38 Derandomized learning of boolean functions
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    Chapter 39 Learning DFA from simple examples
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    Chapter 40 PAC learning under helpful distributions
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    Chapter 41 PAC learning using Nadaraya-Watson estimator based on orthonormal systems
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    Chapter 42 Monotone extensions of boolean data sets
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    Chapter 43 Classical Brouwer-Heyting-Kolmogorov interpretation
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    Chapter 44 Inferring a system from examples with time passage
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    Chapter 45 Polynomial time inductive inference of regular term tree languages from positive data
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    Chapter 46 Synthesizing noise-tolerant language learners
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    Chapter 47 Effects of Kolmogorov complexity present in inductive inference as well
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    Chapter 48 Learning one-variable pattern languages very efficiently on average, in parallel, and by asking queries
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    Chapter 49 Oracles in Σ2p are sufficient for exact learning
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    Chapter 50 Exact learning via teaching assistants (Extended abstract)
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    Chapter 51 An efficient exact learning algorithm for ordered binary decision diagrams
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    Chapter 52 Probability theory for the Brier game
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    Chapter 53 Learning and revising theories in noisy domains
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    Chapter 54 A note on a scale-sensitive dimension of linear bounded functionals in Banach Spaces
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    Chapter 55 On the relevance of time in neural computation and learning
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    Chapter 56 A simple algorithm for predicting nearly as well as the best pruning labeled with the best prediction values of a decision tree
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    Chapter 57 Learning disjunctions of features
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    Chapter 58 Learning simple deterministic finite-memory automata
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    Chapter 59 Learning acyclic first-order horn sentences from entailment
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    Chapter 60 On learning disjunctions of zero-one threshold functions with queries