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Algorithmic Learning Theory: Proceedings Book

Algorithmic Learning Theory: Proceedings
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Algorithmic Learning Theory: Proceedings, This book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995.The book contains 21 revised full papers selected from 46 submissions together with three inv, Algorithmic Learning Theory: Proceedings
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  • Algorithmic Learning Theory: Proceedings
  • Written by author S Kobayashi, K.P. Jantke, Etsuji Tomita, Takashi Yokomori
  • Published by Springer-Verlag, 1993/10/01
  • This book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995.The book contains 21 revised full papers selected from 46 submissions together with three inv
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Authors

Identifying and Using Patterns in Sequential Data 1
Learning Theory Toward Genome Informatics 19
Optimal Layered Learning : A PAC Approach to Incremental Sampling 37
Reformulation of Explanation by Linear Logic - Toward Logic for Explanation 45
Towards Efficient Inductive Synthesis of Expressions from Input/Output Examples 59
A Typed [lambda]-Calculus for Proving-by-Example and Bottom-up Generalization Procedure 73
Case-Based Representation and Learning of Pattern Languages 87
Inductive Resolution 101
Generalized Unification as Background Knowledge in Learning Logic Programs 111
Inductive Inference Machines That Can Refute Hypothesis Spaces 123
On the Duality Between Mechanistic Learners and What it is They Learn 137
On Aggregating Teams of Learning Machines 150
Learning with Growing Quality 164
Use of Reduction Arguments in Determining Popperian FIN-Type Learning Capabilities 173
Properties of Language Classes with Finite Elasticity 187
Uniform Characterizations of Various Kinds of Language Learning 197
How to Invent Characterizable Inference Methods for Regular Languages 209
Neural Discriminant Analysis 223
A New Algorithm for Automatic Configuration of Hidden Markov Models 237
On the VC-Dimension of Depth Four Threshold Circuits and the Complexity of Boolean-valued Functions 251
On the Sample Complexity of Consistent Learning with One-Sided Error 265
Complexity of Computing Vapnik-Chervonenkis Dimension 279
[epsilon]-Approximation of k-Label Spaces 288
Exact Learning of Linear Combinations of Monotone Terms from Function Value Queries 300
Thue Systems and DNA - A Learning Algorithm for a Subclass 314
The VC-Dimensions of Finite Automata with n States 328
Unifying Learning Methods by Colored Digraphs 342
A Perceptual Criterion for Visually Controlling Learning 356
Learning Strategies Using Decision Lists 370
A Decomposition Based Induction Model for Discovering Concept Clusters from Databases 384
Algebraic Structure of Some Learning Systems 398
Induction of Probabilistic Rules Based on Rough Set Theory 410
Index of Authors 424


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Algorithmic Learning Theory: Proceedings, This book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995.The book contains 21 revised full papers selected from 46 submissions together with three inv, Algorithmic Learning Theory: Proceedings

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Algorithmic Learning Theory: Proceedings, This book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995.The book contains 21 revised full papers selected from 46 submissions together with three inv, Algorithmic Learning Theory: Proceedings

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Algorithmic Learning Theory: Proceedings, This book constitutes the refereed proceedings of the 6th International Workshop on Algorithmic Learning Theory, ALT '95, held in Fukuoka, Japan, in October 1995.The book contains 21 revised full papers selected from 46 submissions together with three inv, Algorithmic Learning Theory: Proceedings

Algorithmic Learning Theory: Proceedings

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