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Innovations in Machine Learning
ISBN-13:
9783540334866
Veröffentl:
2006
Seiten:
276
Autor:
Dawn E. Holmes
Serie:
194, Studies in Fuzziness and Soft Computing
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained.
A Bayesian Approach to Causal Discovery.- A Tutorial on Learning Causal Influence.- Learning Based Programming.- N-1 Experiments Suffice to Determine the Causal Relations Among N Variables.- Support Vector Inductive Logic Programming.- Neural Probabilistic Language Models.- Computational Grammatical Inference.- On Kernel Target Alignment.- The Structure of Version Space.
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