Statistical Relational Artificial Intelligence

Author : Luc De Kang,Kristian Chen,Sriraam Yu,David Genesereth
Publisher : Springer Nature
Page : 175 pages
File Size : 40,5 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031015748

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Statistical Relational Artificial Intelligence by Luc De Kang,Kristian Chen,Sriraam Yu,David Genesereth Pdf

An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.

Author : Lise Getoor,Ben Taskar
Publisher : MIT Press
Page : 602 pages
File Size : 50,8 Mb
Release : 2019-09-22
Category : Computers
ISBN : 9780262538688

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Introduction to Statistical Relational Learning by Lise Getoor,Ben Taskar Pdf

Advanced statistical modeling and knowledge representation techniques for a newly emerging area of machine learning and probabilistic reasoning; includes introductory material, tutorials for different proposed approaches, and applications. Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases and programming languages to represent structure. In Introduction to Statistical Relational Learning, leading researchers in this emerging area of machine learning describe current formalisms, models, and algorithms that enable effective and robust reasoning about richly structured systems and data. The early chapters provide tutorials for material used in later chapters, offering introductions to representation, inference and learning in graphical models, and logic. The book then describes object-oriented approaches, including probabilistic relational models, relational Markov networks, and probabilistic entity-relationship models as well as logic-based formalisms including Bayesian logic programs, Markov logic, and stochastic logic programs. Later chapters discuss such topics as probabilistic models with unknown objects, relational dependency networks, reinforcement learning in relational domains, and information extraction. By presenting a variety of approaches, the book highlights commonalities and clarifies important differences among proposed approaches and, along the way, identifies important representational and algorithmic issues. Numerous applications are provided throughout.

Author : Kristian Kersting
Publisher : IOS Press
Page : 258 pages
File Size : 55,5 Mb
Release : 2006
Category : Computers
ISBN : 1586036742

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An Inductive Logic Programming Approach to Statistical Relational Learning by Kristian Kersting Pdf

Talks about Logic Programming, Uncertainty Reasoning and Machine Learning. This book includes definitions that circumscribe the area formed by extending Inductive Logic Programming to cases annotated with probability values. It investigates the approach of Learning from proofs and the issue of upgrading Fisher Kernels to Relational Fisher Kernels.

Author : Kristian Kersting,Stuart Russell,Leslie Pack Kaelbling,Alon Halevy,Sriraam Natarajan,Lilyana Mihalkova
Publisher : Unknown
Page : 110 pages
File Size : 46,8 Mb
Release : 2010-07-11
Category : Electronic
ISBN : 1577354729

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Statistical Relational Artificial Intelligence by Kristian Kersting,Stuart Russell,Leslie Pack Kaelbling,Alon Halevy,Sriraam Natarajan,Lilyana Mihalkova Pdf

Author : Sriraam Natarajan,Kristian Kersting,Tushar Khot,Jude Shavlik
Publisher : Springer
Page : 74 pages
File Size : 45,5 Mb
Release : 2015-03-03
Category : Computers
ISBN : 9783319136448

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Boosted Statistical Relational Learners by Sriraam Natarajan,Kristian Kersting,Tushar Khot,Jude Shavlik Pdf

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.

Author : Luc De Raedt
Publisher : Springer Science & Business Media
Page : 395 pages
File Size : 53,6 Mb
Release : 2008-09-12
Category : Computers
ISBN : 9783540200406

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Logical and Relational Learning by Luc De Raedt Pdf

This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.

Author : Guy Van den Broeck,Kristian Kersting,Sriraam Natarajan,David Poole
Publisher : MIT Press
Page : 455 pages
File Size : 49,7 Mb
Release : 2021-08-17
Category : Computers
ISBN : 9780262542593

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An Introduction to Lifted Probabilistic Inference by Guy Van den Broeck,Kristian Kersting,Sriraam Natarajan,David Poole Pdf

Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field. After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.

Author : Saso Dzeroski,Nada Lavrač
Publisher : Springer Science & Business Media
Page : 410 pages
File Size : 51,6 Mb
Release : 2013-04-17
Category : Computers
ISBN : 9783662045992

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Relational Data Mining by Saso Dzeroski,Nada Lavrač Pdf

As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

Author : Ashwin Srinivasan,Ganesh Ramakrishnan
Publisher : CRC Press
Page : 500 pages
File Size : 52,7 Mb
Release : 2014-01-15
Category : Business & Economics
ISBN : 1439812942

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Handbook of Relational Learning by Ashwin Srinivasan,Ganesh Ramakrishnan Pdf

With increased interest in relational learning and the growing importance of machine learning, artificial intelligence, and data mining, inductive logic programming (ILP)—at the boundary between machine learning and logic programming—is on the rise. Authored by a leading researcher in the field, this timely book provides the first comprehensive introduction to be published in over ten years. It uses an accessible approach to present key concepts in ILP and provide an overview of possible applications. The book covers important topics in the field, including probability and statistics, statistical relational learning, experimental design, and combinatorial algorithms.

Author : David L. Poole,Alan K. Mackworth
Publisher : Cambridge University Press
Page : 821 pages
File Size : 43,5 Mb
Release : 2017-09-25
Category : Computers
ISBN : 9781107195394

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Artificial Intelligence by David L. Poole,Alan K. Mackworth Pdf

Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.

Author : Gautam Kunapuli
Publisher : Simon and Schuster
Page : 350 pages
File Size : 41,8 Mb
Release : 2023-05-02
Category : Computers
ISBN : 9781617297137

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Ensemble Methods for Machine Learning by Gautam Kunapuli Pdf

In Ensemble Methods for Machine Learning you'll learn to implement the most important ensemble machine learning methods from scratch. Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Author : P. Hitzler
Publisher : IOS Press
Page : 410 pages
File Size : 40,9 Mb
Release : 2022-01-19
Category : Computers
ISBN : 9781643682457

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Neuro-Symbolic Artificial Intelligence: The State of the Art by P. Hitzler Pdf

Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. ”Neuro” refers to the artificial neural networks prominent in machine learning, ”symbolic” refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called “third wave” of AI is now bringing them together. This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be. Based on the editors’ own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.

Author : C. Bessiere
Publisher : IOS Press
Page : 1056 pages
File Size : 41,6 Mb
Release : 2012-08-15
Category : Computers
ISBN : 9781614990987

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ECAI 2012 by C. Bessiere Pdf

Artificial intelligence (AI) plays a vital part in the continued development of computer science and informatics. The AI applications employed in fields such as medicine, economics, linguistics, philosophy, psychology and logical analysis, not forgetting industry, are now indispensable for the effective functioning of a multitude of systems. This book presents the papers from the 20th biennial European Conference on Artificial Intelligence, ECAI 2012, held in Montpellier, France, in August 2012. The ECAI conference remains Europe's principal opportunity for researchers and practitioners of Artificial Intelligence to gather and to discuss the latest trends and challenges in all subfields of AI, as well as to demonstrate innovative applications and uses of advanced AI technology. ECAI 2012 featured four keynote speakers, an extensive workshop program, seven invited tutorials and the new Frontiers of Artificial Intelligence track, in which six invited speakers delivered perspective talks on particularly interesting new research results, directions and trends in Artificial Intelligence or in one of its related fields. The proceedings of PAIS 2012 and the System Demonstrations Track are also included in this volume, which will be of interest to all those wishing to keep abreast of the latest developments in the field of AI.

Author : James Seligman
Publisher : Lulu.com
Page : 252 pages
File Size : 50,8 Mb
Release : 2020-02-17
Category : Computers
ISBN : 9780244563882

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artificial Intelligence / Machine Learning In Marketing by James Seligman Pdf

The theory and practice of AI and ML in marketing saving time, money

Author : Gerhard Friedrich,Malte Helmert,Franz Wotawa
Publisher : Springer
Page : 318 pages
File Size : 47,5 Mb
Release : 2016-09-08
Category : Computers
ISBN : 9783319460734

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KI 2016: Advances in Artificial Intelligence by Gerhard Friedrich,Malte Helmert,Franz Wotawa Pdf

This book constitutes the refereed proceedings of the 39th Annual German Conference on Artificial Intelligence, KI 2016, in conjunction with the Österreichische Gesellschaft für Artificial Intelligence, ÖGAI, held in Klagenfurt, Austria, in September 2016. The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions. The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.