Overview
- Dedicated to one of the pioneers in computer science, artificial intelligence and machine learning
- Usage of (universal) Turing machines for prediction problems in statistics, machine learning, econometrics and data mining
- Covers a vast variety of topics such as statistics, econometrics and knowledge discovery, data mining, terabyte science, data science, big data and data management and processing
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7070)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
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Table of contents (35 chapters)
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Long Papers
Keywords
About this book
Editors and Affiliations
Bibliographic Information
Book Title: Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence
Book Subtitle: Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30 -- December 2, 2011
Editors: David L. Dowe
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-642-44958-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Softcover ISBN: 978-3-642-44957-4Published: 11 November 2013
eBook ISBN: 978-3-642-44958-1Published: 22 October 2013
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVI, 445
Number of Illustrations: 61 b/w illustrations
Topics: Computer Science, general
Industry Sectors: IT & Software, Telecommunications