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Computational Trust Models And Machine Learning

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Computational Trust Models And Machine Learning

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Author : Xin Liu
language : en
Publisher: CRC Press
Release Date : 2014-10-29

Computational Trust Models And Machine Learning written by Xin Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-29 with Computers categories.

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: Explains how reputation-based systems are used to determine trust in diverse online communities Describes how machine learning techniques are employed to build robust reputation systems Explores two distinctive approaches to determining credibility of resources—one where the human role is implicit, and one that leverages human input explicitly Shows how decision support can be facilitated by computational trust models Discusses collaborative filtering-based trust aware recommendation systems Defines a framework for translating a trust modeling problem into a learning problem Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.

Computational Trust Models And Machine Learning

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Author : Xin Liu
language : en
Publisher: CRC Press
Release Date : 2014-10-29

Quantum Computing Physics Blockchains And Deep Learning Smart Networks

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Author : Melanie Swan
language : en
Publisher: World Scientific
Release Date : 2020-03-20

Quantum Computing Physics Blockchains And Deep Learning Smart Networks written by Melanie Swan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-20 with Science categories.

Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of current research approaches. Hence, new theories are needed for their understanding and control. Physics is implicated as smart networks are physical systems comprised of particle-many items interacting and reaching criticality and emergence across volumes of macroscopic and microscopic states. Methods are integrated from statistical physics, information theory, and computer science. Statistical neural field theory and the AdS/CFT correspondence are employed to derive a smart network field theory (SNFT) and a smart network quantum field theory (SNQFT) for the orchestration of smart network systems. Specifically, a smart network field theory (conventional or quantum) is a field theory for the organization of particle-many systems from a characterization, control, criticality, and novelty emergence perspective.This book provides insight as to how quantum information science as a paradigm shift in computing may influence other high-impact digital transformation technologies, such as blockchain and machine learning. Smart networks refer to the idea that the internet is no longer simply a communications network, but rather a computing platform. The trajectory is that of communications networks becoming computing networks (with self-executing code), and perhaps ultimately quantum computing networks. Smart network technologies are conceived as autonomous self-operating computing networks. This includes blockchain economies, deep learning neural networks, autonomous supply chains, self-piloting driving fleets, unmanned aerial vehicles, industrial robotics cloudminds, real-time bidding for advertising, high-frequency trading networks, smart city IoT sensors, and the quantum internet.

Machine Learning

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Author : Stephen Marsland
language : en
Publisher: CRC Press
Release Date : 2015-09-15

Machine Learning written by Stephen Marsland and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Computers categories.

A Proven, Hands-On Approach for Students without a Strong Statistical Foundation Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area. Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation. New to the Second Edition Two new chapters on deep belief networks and Gaussian processes Reorganization of the chapters to make a more natural flow of content Revision of the support vector machine material, including a simple implementation for experiments New material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron Additional discussions of the Kalman and particle filters Improved code, including better use of naming conventions in Python Suitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author’s website.

Advanced Methodologies And Technologies In Artificial Intelligence Computer Simulation And Human Computer Interaction

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Author : Khosrow-Pour, D.B.A., Mehdi
language : en
Publisher: IGI Global
Release Date : 2018-09-28

Advanced Methodologies And Technologies In Artificial Intelligence Computer Simulation And Human Computer Interaction written by Khosrow-Pour, D.B.A., Mehdi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-28 with Computers categories.

As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.

Machine Learning

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Author : Mohssen Mohammed
language : en
Publisher: CRC Press
Release Date : 2016-08-19

Machine Learning written by Mohssen Mohammed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-19 with Computers categories.

Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.

Examining Information Retrieval And Image Processing Paradigms In Multidisciplinary Contexts

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Author : Lu, Joan
language : en
Publisher: IGI Global
Release Date : 2017-02-10

Examining Information Retrieval And Image Processing Paradigms In Multidisciplinary Contexts written by Lu, Joan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-10 with Computers categories.

Across numerous industries in modern society, there is a constant need to gather precise and relevant data efficiently and quickly. As such, it is imperative to research new methods and approaches to increase productivity in these areas. Examining Information Retrieval and Image Processing Paradigms in Multidisciplinary Contexts is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as knowledge discovery, spatial indexing, and data mining, this book is ideally designed for researchers, graduate students, academics, and industry professionals seeking ways to optimize knowledge management processes.

Introduction To Machine Learning With Applications In Information Security

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Author : Mark Stamp
language : en
Publisher: CRC Press
Release Date : 2022-09-27

Introduction To Machine Learning With Applications In Information Security written by Mark Stamp and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-27 with Business & Economics categories.

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.

Neural Information Processing

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Author : Tom Gedeon
language : en
Publisher: Springer Nature
Release Date : 2019-12-05

Neural Information Processing written by Tom Gedeon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-05 with Computers categories.

The two-volume set CCIS 1142 and 1143 constitutes thoroughly refereed contributions presented at the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. For ICONIP 2019 a total of 345 papers was carefully reviewed and selected for publication out of 645 submissions. The 168 papers included in this volume set were organized in topical sections as follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred computing; human centred computing and medicine; human centred computing for emotion; hybrid models; image processing by neural techniques; learning from incomplete data; model compression and optimization; neural network applications; neural network models; semantic and graph based approaches; social network computing; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Phealth 2019

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Author : B. Blobel
language : en
Publisher: IOS Press
Release Date : 2019-05-29

Phealth 2019 written by B. Blobel and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-29 with Medical categories.

Smart mobile systems like micro-systems, smart textiles and implants and sensor-controlled medical devices, together with related networks and cloud services, are important enablers for telemedicine and pervasive health to become the next generation of health services. Social media and gamification have added further to pHealth as an ecosystem. This book presents the proceedings of pHealth 2019, the 16th in a series of international conferences on personalized health, held in Genoa, Italy, from 10 – 12 June 2019. The book includes 1 keynote, 2 of 4 invited talks, 36 oral presentations and 7 poster presentations from a total of 141 international authors. All submissions were critically reviewed by at least two independent experts and a member of the Scientific Program Committee. This process resulted in a full paper rejection rate of more than 30%. Besides wearable or implantable micro and nano technologies for personalized medicine, this volume addresses topics such as legal, ethical, social, and organizational requirements and impacts as well as necessary basic research for enabling future proof care paradigms. Such participatory, predictive, personalized, preventive, and effective care settings combine medical services and public health, prevention, social and elderly care, but also wellness and personal fitness. The multilateral benefits of pHealth technologies for all stakeholder communities offer enormous potential for the improvement of both care quality and industrial competitiveness, and also for the management of health care costs. Hence, the book will be of interest to all those involved in the provision of healthcare.

Computational Trust Models And Machine Learning

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