Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 546
Book Description
Preliminary Papers of the Fourth International Workshop on Artificial Intelligence and Statistics
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 546
Book Description
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 546
Book Description
Machine Learning Proceedings 1993
Author: Lawrence A. Birnbaum
Publisher: Morgan Kaufmann
ISBN: 1483298620
Category : Computers
Languages : en
Pages : 361
Book Description
Machine Learning Proceedings 1993
Publisher: Morgan Kaufmann
ISBN: 1483298620
Category : Computers
Languages : en
Pages : 361
Book Description
Machine Learning Proceedings 1993
Data Mining and Machine Learning in Cybersecurity
Author: Sumeet Dua
Publisher: CRC Press
ISBN: 1439839433
Category : Computers
Languages : en
Pages : 248
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
Publisher: CRC Press
ISBN: 1439839433
Category : Computers
Languages : en
Pages : 248
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
Uncertainty in Artificial Intelligence
Author: David Heckerman
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
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.
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
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.
Uncertainty in Artificial Intelligence
Author: MKP
Publisher: Elsevier
ISBN: 1483298604
Category : Computers
Languages : en
Pages : 625
Book Description
Uncertainty Proceedings 1994
Publisher: Elsevier
ISBN: 1483298604
Category : Computers
Languages : en
Pages : 625
Book Description
Uncertainty Proceedings 1994
Learning from Data
Author: Doug Fisher
Publisher: Springer Science & Business Media
ISBN: 1461224047
Category : Mathematics
Languages : en
Pages : 444
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.
Publisher: Springer Science & Business Media
ISBN: 1461224047
Category : Mathematics
Languages : en
Pages : 444
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.
4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering
Author: D. Jude Hemanth
Publisher: Springer Nature
ISBN: 3031319567
Category : Technology & Engineering
Languages : en
Pages : 779
Book Description
As general, this book is a collection of the most recent, quality research papers regarding applications of Artificial Intelligence and Applied Mathematics for engineering problems. The papers included in the book were accepted and presented in the 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022), which was held in Baku, Azerbaijan (Azerbaijan Technical University) between May 20 and 22, 2022. Objective of the book content is to inform the international audience about the cutting-edge, effective developments and improvements in different engineering fields. As a collection of the ICAIAME 2022 event, the book gives consideration for the results by especially intelligent system formations and the associated applications. The target audience of the book is international researchers, degree students, practitioners from industry, and experts from different engineering disciplines.
Publisher: Springer Nature
ISBN: 3031319567
Category : Technology & Engineering
Languages : en
Pages : 779
Book Description
As general, this book is a collection of the most recent, quality research papers regarding applications of Artificial Intelligence and Applied Mathematics for engineering problems. The papers included in the book were accepted and presented in the 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022), which was held in Baku, Azerbaijan (Azerbaijan Technical University) between May 20 and 22, 2022. Objective of the book content is to inform the international audience about the cutting-edge, effective developments and improvements in different engineering fields. As a collection of the ICAIAME 2022 event, the book gives consideration for the results by especially intelligent system formations and the associated applications. The target audience of the book is international researchers, degree students, practitioners from industry, and experts from different engineering disciplines.
Proceedings
Author: Rakesh Agrawal
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 396
Book Description
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 396
Book Description
Uncertainty in Artificial Intelligence
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 566
Book Description
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 566
Book Description
Emerging Information Security and Applications
Author: Jun Shao
Publisher: Springer Nature
ISBN: 9819996147
Category : Computers
Languages : en
Pages : 195
Book Description
This volume constitutes the proceedings presented at the 4th International Conference on Emerging Information Security and Applications, EISA 2023, held in Hangzhou, China, in December 2023. The 11 full papers presented in this volume were thoroughly reviewed and selected from the 35 submissions. The topics of the book are related but not limited to cyber intelligence techniques, multimedia security, blockchain and distributed ledger technology, malware and unwanted software, vulnerability analysis and reverse engineering, usable security and privacy, intrusion detection and prevention, authentication and access control, anonymity and privacy, cryptographic protection, digital forensics, cyber physical systems security, adversarial learning, security measurement, security management and policies, hardware and physical security.
Publisher: Springer Nature
ISBN: 9819996147
Category : Computers
Languages : en
Pages : 195
Book Description
This volume constitutes the proceedings presented at the 4th International Conference on Emerging Information Security and Applications, EISA 2023, held in Hangzhou, China, in December 2023. The 11 full papers presented in this volume were thoroughly reviewed and selected from the 35 submissions. The topics of the book are related but not limited to cyber intelligence techniques, multimedia security, blockchain and distributed ledger technology, malware and unwanted software, vulnerability analysis and reverse engineering, usable security and privacy, intrusion detection and prevention, authentication and access control, anonymity and privacy, cryptographic protection, digital forensics, cyber physical systems security, adversarial learning, security measurement, security management and policies, hardware and physical security.