Computational Learning Theory and Natural Learning Systems: Making learning systems practical

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Publisher : MIT Press
ISBN 13 : 9780262571180
Total Pages : 440 pages
Book Rating : 4.5/5 (711 download)

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Book Synopsis Computational Learning Theory and Natural Learning Systems: Making learning systems practical by : Russell Greiner

Download or read book Computational Learning Theory and Natural Learning Systems: Making learning systems practical written by Russell Greiner and published by MIT Press. This book was released on 1994 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the fourth and final volume of papers from a series of workshops called "Computational Learning Theory and Ǹatural' Learning Systems." The purpose of the workshops was to explore the emerging intersection of theoretical learning research and natural learning systems. The workshops drew researchers from three historically distinct styles of learning research: computational learning theory, neural networks, and machine learning (a subfield of AI). Volume I of the series introduces the general focus of the workshops. Volume II looks at specific areas of interaction between theory and experiment. Volumes III and IV focus on key areas of learning systems that have developed recently. Volume III looks at the problem of "Selecting Good Models." The present volume, Volume IV, looks at ways of "Making Learning Systems Practical." The editors divide the twenty-one contributions into four sections. The first three cover critical problem areas: 1) scaling up from small problems to realistic ones with large input dimensions, 2) increasing efficiency and robustness of learning methods, and 3) developing strategies to obtain good generalization from limited or small data samples. The fourth section discusses examples of real-world learning systems. Contributors : Klaus Abraham-Fuchs, Yasuhiro Akiba, Hussein Almuallim, Arunava Banerjee, Sanjay Bhansali, Alvis Brazma, Gustavo Deco, David Garvin, Zoubin Ghahramani, Mostefa Golea, Russell Greiner, Mehdi T. Harandi, John G. Harris, Haym Hirsh, Michael I. Jordan, Shigeo Kaneda, Marjorie Klenin, Pat Langley, Yong Liu, Patrick M. Murphy, Ralph Neuneier, E.M. Oblow, Dragan Obradovic, Michael J. Pazzani, Barak A. Pearlmutter, Nageswara S.V. Rao, Peter Rayner, Stephanie Sage, Martin F. Schlang, Bernd Schurmann, Dale Schuurmans, Leon Shklar, V. Sundareswaran, Geoffrey Towell, Johann Uebler, Lucia M. Vaina, Takefumi Yamazaki, Anthony M. Zador.

Computational Learning Theory and Natural Learning Systems

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Publisher :
ISBN 13 :
Total Pages : 550 pages
Book Rating : 4.:/5 (93 download)

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Book Synopsis Computational Learning Theory and Natural Learning Systems by : Stephen José Hanson

Download or read book Computational Learning Theory and Natural Learning Systems written by Stephen José Hanson and published by . This book was released on 1994 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Boosting

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Publisher : MIT Press
ISBN 13 : 0262526034
Total Pages : 544 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Boosting by : Robert E. Schapire

Download or read book Boosting written by Robert E. Schapire and published by MIT Press. This book was released on 2014-01-10 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

Algorithmic Learning Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 3540233563
Total Pages : 519 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Algorithmic Learning Theory by : Shai Ben David

Download or read book Algorithmic Learning Theory written by Shai Ben David and published by Springer Science & Business Media. This book was released on 2004-09-23 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic learning theory is mathematics about computer programs which learn from experience. This involves considerable interaction between various mathematical disciplines including theory of computation, statistics, and c- binatorics. There is also considerable interaction with the practical, empirical ?elds of machine and statistical learning in which a principal aim is to predict, from past data about phenomena, useful features of future data from the same phenomena. The papers in this volume cover a broad range of topics of current research in the ?eld of algorithmic learning theory. We have divided the 29 technical, contributed papers in this volume into eight categories (corresponding to eight sessions) re?ecting this broad range. The categories featured are Inductive Inf- ence, Approximate Optimization Algorithms, Online Sequence Prediction, S- tistical Analysis of Unlabeled Data, PAC Learning & Boosting, Statistical - pervisedLearning,LogicBasedLearning,andQuery&ReinforcementLearning. Below we give a brief overview of the ?eld, placing each of these topics in the general context of the ?eld. Formal models of automated learning re?ect various facets of the wide range of activities that can be viewed as learning. A ?rst dichotomy is between viewing learning as an inde?nite process and viewing it as a ?nite activity with a de?ned termination. Inductive Inference models focus on inde?nite learning processes, requiring only eventual success of the learner to converge to a satisfactory conclusion.

Advancing Socio-Economics

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Publisher : Rowman & Littlefield
ISBN 13 : 9780742511774
Total Pages : 470 pages
Book Rating : 4.5/5 (117 download)

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Book Synopsis Advancing Socio-Economics by : Karl H. Müller

Download or read book Advancing Socio-Economics written by Karl H. Müller and published by Rowman & Littlefield. This book was released on 2005 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this landmark volume, J. Rodgers Hollingsworth, Karl H. M ller, and Ellen Jane Hollingsworth take a first step towards imposing order on the increasingly diverse field of socio-economics by embedding the various disciplines and sub-disciplines in a common core. The distinguished contributors in this volume show how institutions, governance arrangements, societal sectors, organizations, individual actors, and innovativeness are intertwined and, ultimately, how individuals and firms have a high degree of autonomy. By offering original suggestions and guidelines for developing a socio-economics research agenda focused on institutional analysis, Advancing Socio-Economics: An Institutionalist Perspective, will enlighten all interested in the social sciences.

Foundations of Machine Learning, second edition

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Publisher : MIT Press
ISBN 13 : 0262351366
Total Pages : 505 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Foundations of Machine Learning, second edition by : Mehryar Mohri

Download or read book Foundations of Machine Learning, second edition written by Mehryar Mohri and published by MIT Press. This book was released on 2018-12-25 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.

Cost-Sensitive Machine Learning

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Publisher : CRC Press
ISBN 13 : 143983928X
Total Pages : 316 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Cost-Sensitive Machine Learning by : Balaji Krishnapuram

Download or read book Cost-Sensitive Machine Learning written by Balaji Krishnapuram and published by CRC Press. This book was released on 2011-12-19 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/attributes for test dataCost of user feedback collect

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

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Publisher :
ISBN 13 :
Total Pages : 356 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Proceedings of the ... Annual ACM Conference on Computational Learning Theory by :

Download or read book Proceedings of the ... Annual ACM Conference on Computational Learning Theory written by and published by . This book was released on 1999 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

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Publisher :
ISBN 13 :
Total Pages : 348 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Proceedings of the ... Annual Conference on Computational Learning Theory by :

Download or read book Proceedings of the ... Annual Conference on Computational Learning Theory written by and published by . This book was released on 1999 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Probably Approximately Correct

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Publisher : Basic Books (AZ)
ISBN 13 : 0465032710
Total Pages : 210 pages
Book Rating : 4.4/5 (65 download)

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Book Synopsis Probably Approximately Correct by : Leslie Valiant

Download or read book Probably Approximately Correct written by Leslie Valiant and published by Basic Books (AZ). This book was released on 2013-06-04 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a theory of the theoryless, a computer scientist provides a model of how effective behavior can be learned even in a world as complex as our own, shedding new light on human nature.

Explainable AI and Other Applications of Fuzzy Techniques

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Publisher : Springer Nature
ISBN 13 : 3030820998
Total Pages : 506 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Explainable AI and Other Applications of Fuzzy Techniques by : Julia Rayz

Download or read book Explainable AI and Other Applications of Fuzzy Techniques written by Julia Rayz and published by Springer Nature. This book was released on 2021-07-27 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.

Neural Computation

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Publisher :
ISBN 13 :
Total Pages : 958 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural Computation by :

Download or read book Neural Computation written by and published by . This book was released on 1996 with total page 958 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers neural computation, which encompasses psychology, physics, computer science, neuroscience, and artificial intelligence, among others. It highlights common problems and techniques in modeling the brain, and the design and construction of neurally inspired information processing systems.

Multisector Insights in Healthcare, Social Sciences, Society, and Technology

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Publisher : IGI Global
ISBN 13 :
Total Pages : 409 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Multisector Insights in Healthcare, Social Sciences, Society, and Technology by : Burrell, Darrell Norman

Download or read book Multisector Insights in Healthcare, Social Sciences, Society, and Technology written by Burrell, Darrell Norman and published by IGI Global. This book was released on 2024-02-27 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to a variety of global challenges in recent times, the dissolution of traditional boundaries between academic disciplines has given rise to a pressing need for innovative problem-solving. Complex issues affect our societies, spanning healthcare, social sciences, organizational behavior, and technology. This shifting landscape necessitates a comprehensive exploration into the interconnections between these diverse fields. The book, Multisector Insights in Healthcare, Social Sciences, Society, and Technology, is an innovative guide that seeks to examine the relationships between various fields of knowledge. It celebrates the transformative impact of applied research and interdisciplinary collaboration as the driving force behind overcoming the most significant challenges of our time. As the boundaries between disciplines blur, the book takes readers on a journey through multifaceted issues at the intersection of healthcare, social sciences, organizational behavior, and technology. Chapters within this book unravel the complexities of healthcare ethics, global health initiatives, organizational dynamics, and technological advancements. Through literature reviews, qualitative and quantitative studies, and real-world case analyses, the compendium not only identifies the problems but also offers concrete, evidence-backed solutions. This interdisciplinary approach underscores the need to address the pressing challenges of our time, emphasizing the need for collaborative strategies to drive positive change.

A Nature-Inspired Approach to Cryptology

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Publisher : Springer Nature
ISBN 13 : 9819970814
Total Pages : 325 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis A Nature-Inspired Approach to Cryptology by : Shishir Kumar Shandilya

Download or read book A Nature-Inspired Approach to Cryptology written by Shishir Kumar Shandilya and published by Springer Nature. This book was released on 2024-01-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces nature-inspired algorithms and their applications to modern cryptography. It helps the readers to get into the field of nature-based approaches to solve complex cryptographic issues. This book provides a comprehensive view of nature-inspired research which could be applied in cryptography to strengthen security. It will also explore the novel research directives such as Clever algorithms and immune-based cyber resilience. New experimented nature-inspired approaches are having enough potential to make a huge impact in the field of cryptanalysis. This book gives a lucid introduction to this exciting new field and will promote further research in this domain. The book discusses the current landscape of cryptography and nature-inspired research and will be helpful to prospective students and professionals to explore further.

From Molecule to Metaphor

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Publisher : MIT Press
ISBN 13 : 0262296888
Total Pages : 758 pages
Book Rating : 4.2/5 (622 download)

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Book Synopsis From Molecule to Metaphor by : Jerome Feldman

Download or read book From Molecule to Metaphor written by Jerome Feldman and published by MIT Press. This book was released on 2008-01-25 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: In From Molecule to Metaphor, Jerome Feldman proposes a theory of language and thought that treats language not as an abstract symbol system but as a human biological ability that can be studied as a function of the brain, as vision and motor control are studied. This theory, he writes, is a "bridging theory" that works from extensive knowledge at two ends of a causal chain to explicate the links between. Although the cognitive sciences are revealing much about how our brains produce language and thought, we do not yet know exactly how words are understood or have any methodology for finding out. Feldman develops his theory in computer simulations—formal models that suggest ways that language and thought may be realized in the brain. Combining key findings and theories from biology, computer science, linguistics, and psychology, Feldman synthesizes a theory by exhibiting programs that demonstrate the required behavior while remaining consistent with the findings from all disciplines. After presenting the essential results on language, learning, neural computation, the biology of neurons and neural circuits, and the mind/brain, Feldman introduces specific demonstrations and formal models of such topics as how children learn their first words, words for abstract and metaphorical concepts, understanding stories, and grammar (including "hot-button" issues surrounding the innateness of human grammar). With this accessible, comprehensive book Feldman offers readers who want to understand how our brains create thought and language a theory of language that is intuitively plausible and also consistent with existing scientific data at all levels.

Learning to Learn

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Publisher : Springer Science & Business Media
ISBN 13 : 1461555299
Total Pages : 346 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Learning to Learn by : Sebastian Thrun

Download or read book Learning to Learn written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past three decades or so, research on machine learning and data mining has led to a wide variety of algorithms that learn general functions from experience. As machine learning is maturing, it has begun to make the successful transition from academic research to various practical applications. Generic techniques such as decision trees and artificial neural networks, for example, are now being used in various commercial and industrial applications. Learning to Learn is an exciting new research direction within machine learning. Similar to traditional machine-learning algorithms, the methods described in Learning to Learn induce general functions from experience. However, the book investigates algorithms that can change the way they generalize, i.e., practice the task of learning itself, and improve on it. To illustrate the utility of learning to learn, it is worthwhile comparing machine learning with human learning. Humans encounter a continual stream of learning tasks. They do not just learn concepts or motor skills, they also learn bias, i.e., they learn how to generalize. As a result, humans are often able to generalize correctly from extremely few examples - often just a single example suffices to teach us a new thing. A deeper understanding of computer programs that improve their ability to learn can have a large practical impact on the field of machine learning and beyond. In recent years, the field has made significant progress towards a theory of learning to learn along with practical new algorithms, some of which led to impressive results in real-world applications. Learning to Learn provides a survey of some of the most exciting new research approaches, written by leading researchers in the field. Its objective is to investigate the utility and feasibility of computer programs that can learn how to learn, both from a practical and a theoretical point of view.

Agents and Artificial Intelligence

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Publisher : Springer
ISBN 13 : 3642299660
Total Pages : 454 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Agents and Artificial Intelligence by : Joaquim Filipe

Download or read book Agents and Artificial Intelligence written by Joaquim Filipe and published by Springer. This book was released on 2013-01-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Agents and Artificial Intelligence, ICAART 2011, held in Rome, Italy, in January 2011. The 26 revised full papers presented together with two invited paper were carefully reviewed and selected from 367 submissions. The papers are organized in two topical sections on artificial intelligence and on agents.