Weighing Hypothesis: Incremental Learning from Noisy Data

Weighing Hypothesis: Incremental Learning from Noisy Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 12

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Weighing Hypothesis: Incremental Learning from Noisy Data

Weighing Hypothesis: Incremental Learning from Noisy Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 12

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A Model of Sequence Extrapolation

A Model of Sequence Extrapolation PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 14

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Proceedings of the ... Annual ACM Conference on Computational Learning Theory

Proceedings of the ... Annual ACM Conference on Computational Learning Theory PDF Author:
Publisher:
ISBN:
Category : Machine learning
Languages : en
Pages : 380

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Inductive Logic Programming

Inductive Logic Programming PDF Author: Filip Železný
Publisher: Springer Science & Business Media
ISBN: 3540859276
Category : Computers
Languages : en
Pages : 358

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Book Description
This book constitutes the refereed proceedings of the 18th International Conference on Inductive Logic Programming, ILP 2008, held in Prague, Czech Republic, in September 2008. The 20 revised full papers presented together with the abstracts of 5 invited lectures were carefully reviewed and selected during two rounds of reviewing and improvement from 46 initial submissions. All current topics in inductive logic programming are covered, ranging from theoretical and methodological issues to advanced applications. The papers present original results in the first-order logic representation framework, explore novel logic induction frameworks, and address also new areas such as statistical relational learning, graph mining, or the semantic Web.

In Order to Learn

In Order to Learn PDF Author: Frank E. Ritter
Publisher: Oxford University Press
ISBN: 0198039778
Category : Psychology
Languages : en
Pages : 255

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Book Description
Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning.

Design and Analysis of Learning Classifier Systems

Design and Analysis of Learning Classifier Systems PDF Author: Jan Drugowitsch
Publisher: Springer
ISBN: 3540798668
Category : Computers
Languages : en
Pages : 274

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Book Description
This book is probably best summarized as providing a principled foundation for Learning Classi?er Systems. Something is happening in LCS, and particularly XCS and its variants that clearly often produces good results. Jan Drug- itsch wishes to understand this from a broader machine learning perspective and thereby perhaps to improve the systems. His approach centers on choosing a statistical de?nition – derived from machine learning – of “a good set of cl- si?ers”, based on a model according to which such a set represents the data. For an illustration of this approach, he designs the model to be close to XCS, and tests it by evolving a set of classi?ers using that de?nition as a ?tness criterion, seeing ifthe setprovidesa goodsolutionto twodi?erent function approximation problems. It appears to, meaning that in some sense his de?nition of “good set of classi?ers” (also, in his terms, a good model structure) captures the essence, in machine learning terms, of what XCS is doing. In the process of designing the model, the author describes its components and their training in clear detail and links it to currently used LCS, giving rise to recommendations for how those LCS can directly gain from the design of the model and its probabilistic formulation. The seeming complexity of evaluating the quality ofa set ofclassi?ersis alleviatedby giving analgorithmicdescription of how to do it, which is carried out via a simple Pittsburgh-style LCS.

Machine Learning

Machine Learning PDF Author: Yves Kodratoff
Publisher: Morgan Kaufmann
ISBN: 9781558601192
Category : Computers
Languages : en
Pages : 840

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Book Description
One of the largest and most active areas of AI, machine learning is of interest to students of psychology, philosophy of science, and education. Although self-contained, volume III follows the tradition of volume I (1983) and volume II (1986). Annotation copyrighted by Book News, Inc., Portland, OR

Machine Learning: ECML-95

Machine Learning: ECML-95 PDF Author: Nada Lavrač
Publisher: Springer Science & Business Media
ISBN: 9783540592860
Category : Computers
Languages : en
Pages : 388

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Book Description
This volume constitutes the proceedings of the Eighth European Conference on Machine Learning ECML-95, held in Heraclion, Crete in April 1995. Besides four invited papers the volume presents revised versions of 14 long papers and 26 short papers selected from a total of 104 submissions. The papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.

Industrial Applications of Machine Learning

Industrial Applications of Machine Learning PDF Author: Pedro Larrañaga
Publisher: CRC Press
ISBN: 1351128361
Category : Business & Economics
Languages : en
Pages : 309

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Book Description
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Medical Data Analysis

Medical Data Analysis PDF Author: Rüdiger W. Brause
Publisher: Springer
ISBN: 3540399496
Category : Computers
Languages : en
Pages : 327

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Book Description
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zing patient data, even in smaller health care institutions, the need for a rational treatment of all these data emerged as well. Therefore, the need for data exchange and presentation systems grew also. The goal of the symposium is to collect all these relevant aspects together. It provides an international forum for the sharing and exchange of original re- arch results, ideas and practical experiences among researchers and application developers from di erent areas related to medical applications dealing with the analysis of medical data. After a thorough reviewing process, 33 high quality papers were selected from the 45 international submissions. These contributions provided the di erent - pects of the eld in order to represent us with an exciting program.