Preliminary Papers of the Fourth International Workshop on Artificial Intelligence and Statistics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Preliminary Papers of the Fourth International Workshop on Artificial Intelligence and Statistics PDF full book. Access full book title Preliminary Papers of the Fourth International Workshop on Artificial Intelligence and Statistics by . Download full books in PDF and EPUB format.
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 546
Get Book
Book Description
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 546
Get Book
Book Description
Author: David Heckerman
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
Get Book
Book Description
Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
Author: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
ISBN: 1483298620
Category : Computers
Languages : en
Pages : 540
Get Book
Book Description
Machine Learning Proceedings 1993
Author: Sumeet Dua
Publisher: CRC Press
ISBN: 1439839433
Category : Computers
Languages : en
Pages : 256
Get Book
Book Description
With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible
Author: Doug Fisher
Publisher: Springer Science & Business Media
ISBN: 1461224047
Category : Mathematics
Languages : en
Pages : 444
Get Book
Book Description
Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.
Author: MKP
Publisher: Elsevier
ISBN: 1483298604
Category : Computers
Languages : en
Pages : 625
Get Book
Book Description
Uncertainty Proceedings 1994
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 566
Get Book
Book Description
Author: Fedja Hadzic
Publisher: Springer
ISBN: 3642175570
Category : Computers
Languages : en
Pages : 340
Get Book
Book Description
Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.
Author: Lorenza Saitta
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 580
Get Book
Book Description
Author: Canadian Society for Computational Studies of Intelligence. Conference
Publisher: Springer Science & Business Media
ISBN: 3540220046
Category : Computers
Languages : en
Pages : 595
Get Book
Book Description
This book constitutes the refereed proceedings of the 17th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2004, held in London, Ontario, Canada in May 2004. The 29 revised full papers and 22 revised short papers were carefully reviewed and selected from 105 submissions. These papers are presented together with the extended abstracts of 14 contributions to the graduate students' track. The full papers are organized in topical sections on agents, natural language processing, learning, constraint satisfaction and search, knowledge representation and reasoning, uncertainty, and neural networks.
