Real World Reasoning Toward Scalable Uncertain Spatiotemporal Contextual And Causal Inference
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Real World Reasoning
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Author :
language : en
Publisher:
Release Date : 2011-12-03
Real World Reasoning written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-03 with categories.
Real World Reasoning Toward Scalable Uncertain Spatiotemporal Contextual And Causal Inference
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Author : Ben Goertzel
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-12-02
Real World Reasoning Toward Scalable Uncertain Spatiotemporal Contextual And Causal Inference written by Ben Goertzel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-02 with Computers categories.
The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses – querying, data mining, data analysis – is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.
Integration Of World Knowledge For Natural Language Understanding
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Author : Ekaterina Ovchinnikova
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-15
Integration Of World Knowledge For Natural Language Understanding written by Ekaterina Ovchinnikova and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Computers categories.
This book concerns non-linguistic knowledge required to perform computational natural language understanding (NLU). The main objective of the book is to show that inference-based NLU has the potential for practical large scale applications. First, an introduction to research areas relevant for NLU is given. We review approaches to linguistic meaning, explore knowledge resources, describe semantic parsers, and compare two main forms of inference: deduction and abduction. In the main part of the book, we propose an integrative knowledge base combining lexical-semantic, ontological, and distributional knowledge. A particular attention is payed to ensuring its consistency. We then design a reasoning procedure able to make use of the large scale knowledge base. We experiment both with a deduction-based NLU system and with an abductive reasoner. For evaluation, we use three different NLU tasks: recognizing textual entailment, semantic role labeling, and interpretation of noun dependencies.
Ethics And Security Automata
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Author : Sean Welsh
language : en
Publisher: Routledge
Release Date : 2017-11-06
Ethics And Security Automata written by Sean Welsh and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-06 with Political Science categories.
Can security automata (robots and AIs) make moral decisions to apply force on humans correctly? If they can make such decisions, ought they be used to do so? Will security automata increase or decrease aggregate risk to humans? What regulation is appropriate? Addressing these important issues this book examines the political and technical challenges of the robotic use of force. The book presents accessible practical examples of the ‘machine ethics’ technology likely to be installed in military and police robots and also in civilian robots with everyday security functions such as childcare. By examining how machines can pass ‘reasonable person’ tests to demonstrate measurable levels of moral competence and display the ability to determine the ‘spirit’ as well as the ‘letter of the law’, the author builds upon existing research to define conditions under which robotic force can and ought to be used to enhance human security. The scope of the book is thus far broader than ‘shoot to kill’ decisions by autonomous weapons, and should attract readers from the fields of ethics, politics, and legal, military and international affairs. Researchers in artificial intelligence and robotics will also find it useful.
Theoretical Foundations Of Artificial General Intelligence
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Author : Pei Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-31
Theoretical Foundations Of Artificial General Intelligence written by Pei Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-31 with Computers categories.
This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines
Federated Learning
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Author : Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Federated Learning written by Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Ecological Inference
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Author : Gary King
language : en
Publisher: Cambridge University Press
Release Date : 2004-09-13
Ecological Inference written by Gary King and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-13 with Nature categories.
Drawing upon the recent explosion of research in the field, a diverse group of scholars surveys the latest strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays offers many fresh and important contributions to the study of ecological inference.
Optimization For Machine Learning
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Author : Suvrit Sra
language : en
Publisher: MIT Press
Release Date : 2012
Optimization For Machine Learning written by Suvrit Sra and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.
2020 Ieee Cvf Conference On Computer Vision And Pattern Recognition Cvpr
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2020-06-13
2020 Ieee Cvf Conference On Computer Vision And Pattern Recognition Cvpr written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-13 with categories.
CVPR is the premier annual computer vision event comprising the main conference and several co located workshops and short courses With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers
Sequence Learning
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Author : Ron Sun
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-01-10
Sequence Learning written by Ron Sun and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-01-10 with Computers categories.
Sequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. This book presents coherently integrated chapters by leading authorities and assesses the state of the art in sequence learning by introducing essential models and algorithms and by examining a variety of applications. The book offers topical sections on sequence clustering and learning with Markov models, sequence prediction and recognition with neural networks, sequence discovery with symbolic methods, sequential decision making, biologically inspired sequence learning models.