3 edition of **Algorithmic learning theory** found in the catalog.

Algorithmic learning theory

ALT 2008 (2008 Budapest, Hungary)

- 17 Want to read
- 34 Currently reading

Published
**2008**
by Springer in Berlin, New York
.

Written in English

- Computer algorithms -- Congresses,
- Machine learning -- Congresses

**Edition Notes**

Includes bibliographical references and index.

Statement | Yoav Freund ... [et al.] (eds.). |

Genre | Congresses |

Series | Lecture notes in computer science -- 5254. Lecture notes in artificial intelligence |

Contributions | Freund, Yoav. |

Classifications | |
---|---|

LC Classifications | QA76.9.A43 A48 2008 |

The Physical Object | |

Pagination | xiii, 466 p. : |

Number of Pages | 466 |

ID Numbers | |

Open Library | OL23908680M |

ISBN 10 | 3540879862 |

ISBN 10 | 9783540879862 |

LC Control Number | 2008936817 |

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Mar 01, · Understanding Machine Learning Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a princi-pled . To understand the current limitations of Deep Learning in medicine, one should start with a general theory of clinical decsion making. One such theory called Dual Process Theory has been proposed by Daniel Kahneman in his book Thinking, Fast and Slow. Pat Croskerry has written extensively about the application of Dual Process Theory to clinical.

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Algorithmic learning theory is a mathematical framework for analyzing machine learning problems and algorithms. Synonyms include formal learning theory and algorithmic inductive inference. Algorithmic learning theory is different from statistical learning theory in that it does not make use of statistical assumptions and analysis.

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Algorithmic Game Theory develops the central ideas and results of this new and exciting area. This book constitutes the proceedings of the 25th International Conference on Algorithmic Learning Theory, ALTheld in Bled, Slovenia, in Octoberand co-located with the 17th International Conference on Discovery Science, DS The 21 papers presented in this volume were carefully.

Introduction to Algorithmic Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers.

It summarizes various techniques tested by major technology, advertising, and retail companies, and it glues these methods together with economic theory and machine learning. This is the first book to collect essays from philosophers, mathematicians and computer scientists working at the exciting interface of algorithmic learning theory and the epistemology of science and inductive inference.

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Topics covered in the papers selected in this book include neural networks, inductive inference, analogical Read more. This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALTheld in Singapore in Octoberand co-located with the 16th International Conference on Discovery Science, DS The 23 papers presented in this volume were carefully reviewed and selected from 39 submissions.

Now the book is published, these files will remain viewable on this website. The same copyright rules will apply to the online copy of the book as apply to normal books. [e.g., copying the whole book onto paper is not permitted.] History: Draft - March 14 Draft - April 4 Draft - April 9 Draft - April Algorithmic learning in a random world (Springer, New York, ) is a book about conformal prediction, a method that combines the power of modern machine learning, especially as applied to high-dimensional data sets, with the informative and valid measures of confidence.

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Jantke (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders. This book constitutes the proceedings of the 26th International Conference on Algorithmic Learning Theory, ALTheld in Banff, AB, Canada, in Octoberand co-located with the 18th International Conference on Discovery Science, DS The 23 full papers presented in this volume were carefully reviewed and selected from 44 submissions.

My research interests include topics in machine learning, algorithmic game theory and microeconomics, computational social science, and quantitative finance and algorithmic trading. I often examine problems in these areas using methods and models from theoretical computer science and related disciplines.This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALTheld in Bari, Italy, in Octoberco-located with the 19th Internation.This book constitutes the conference proceedings of the 5th International Conference on Algorithmic Decision Theory, ADTheld in Luxembourg, in October The 22 full papers presented together with 6 short papers, 4 keynote abstracts, and 6 Doctoral .