Learning From Data Streams In Evolving Environments
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Learning From Data Streams In Evolving Environments
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer
Release Date : 2018-07-28
Learning From Data Streams In Evolving Environments written by Moamar Sayed-Mouchaweh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-28 with Technology & Engineering categories.
This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.
Machine Learning For Data Streams
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Author : Albert Bifet
language : en
Publisher: MIT Press
Release Date : 2018-03-16
Machine Learning For Data Streams written by Albert Bifet and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-16 with Computers categories.
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.
Proceedings Of The 2nd International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2022-01-10
Proceedings Of The 2nd International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-10 with Technology & Engineering categories.
This book contains original, peer-reviewed research articles from the Second International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, held in March 28-29th 2021 at CMR Institute of Technology, Hyderabad, Telangana India. It covers the latest research trends and developments in areas of machine learning, artificial intelligence, neural networks, cyber-physical systems, cybernetics, with emphasis on applications in smart cities, Internet of Things, practical data science and cognition. The book focuses on the comprehensive tenets of artificial intelligence, machine learning and deep learning to emphasize its use in modelling, identification, optimization, prediction, forecasting and control of future intelligent systems. Submissions were solicited of unpublished material, and present in-depth fundamental research contributions from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving a diverse range of problems in industries and its real-world applications.
Ecml Pkdd 2018 Workshops
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Author : Anna Monreale
language : en
Publisher: Springer
Release Date : 2019-03-07
Ecml Pkdd 2018 Workshops written by Anna Monreale and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-07 with Computers categories.
This book constitutes revised selected papers from the workshops DMLE and IoTStream, held at the 18thEuropean Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018. The 8 full papers presented in this volume were carefully reviewed and selected from a total of 12 submissions. The workshops included are: DMLE 2018: First Workshop on Decentralized Machine Learning at the Edge IoTStream 2018: 3rd Workshop on IoT Large Scale Machine Learning from Data Streams
Learning In Non Stationary Environments
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-13
Learning In Non Stationary Environments written by Moamar Sayed-Mouchaweh 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 2012-04-13 with Technology & Engineering categories.
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy. Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations. This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research.
Smart Embedded Systems
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Author : Arun Sinha
language : en
Publisher: CRC Press
Release Date : 2023-12-01
Smart Embedded Systems written by Arun Sinha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Technology & Engineering categories.
"Smart Embedded Systems: Advances and Applications" is a comprehensive guide that demystifies the complex world of embedded technology. The book journeys through a wide range of topics from healthcare to energy management, autonomous robotics, and wireless communication, showcasing the transformative potential of intelligent embedded systems in these fields. This concise volume introduces readers to innovative techniques and their practical applications, offers a comparative analysis of wireless protocols, and provides efficient resource allocation strategies in IoT-based ecosystems. With real-world examples and in-depth case studies, it serves as an invaluable resource for students and professionals seeking to harness the power of embedded technology to shape our digital future. Salient Features: The book provides a comprehensive coverage of various aspects of smart embedded systems, exploring their design, implementation, optimization, and a range of applications. This is further enhanced by in-depth discussions on hardware and software optimizations aimed at improving overall system performance. A detailed examination of machine learning techniques specifically tailored for data analysis and prediction within embedded systems. This complements the exploration of cutting-edge research on the use of AI to enhance wireless communications. Real-world applications of these technologies are extensively discussed, with a focus on areas such as seizure detection, noise reduction, health monitoring, diabetic care, autonomous vehicles, and communication systems. This includes a deep-dive into different wireless protocols utilized for data transfer in IoT systems. This book highlights key IoT technologies and their myriad applications, extending from environmental data collection to health monitoring. This is underscored by case studies on the integration of AI and IoT in healthcare, spanning topics from anomaly detection to informed clinical decision-making. Also featured is a detailed evaluation and comparison of different system implementations and methodologies This book is an essential read for anyone interested in the field of embedded systems. Whether you're a student looking to broaden your knowledge base, researchers looking in-depth insights, or professionals planning to use this cutting-edge technology in real-world applications, this book offers a thorough grounding in the subject.
Proceeding Of 2022 International Conference On Wireless Communications Networking And Applications Wcna 2022
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Author : Zhihong Qian
language : en
Publisher: Springer Nature
Release Date : 2023-07-26
Proceeding Of 2022 International Conference On Wireless Communications Networking And Applications Wcna 2022 written by Zhihong Qian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Technology & Engineering categories.
This proceedings includes original, unpublished, peer-reviewed research papers from the International Conference on Wireless Communications, Networking and Applications (WCNA2022), held in Wuhan, Hubei, China, from December 16 to 18, 2022. The topics covered include but are not limited to wireless communications, networking and applications. The papers showcased here share the latest findings on methodologies, algorithms and applications in communication and network, making the book a valuable asset for professors, researchers, engineers, and university students alike.
Learning From Data Streams
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Author : João Gama
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-20
Learning From Data Streams written by João Gama 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 2007-09-20 with Computers categories.
Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.
Knowledge Discovery From Data Streams
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Author : Joao Gama
language : en
Publisher: CRC Press
Release Date : 2010-05-25
Knowledge Discovery From Data Streams written by Joao Gama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-25 with Business & Economics categories.
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.
Sustained Simulation Performance 2019 And 2020
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Author : Michael M. Resch
language : en
Publisher: Springer Nature
Release Date : 2021-03-01
Sustained Simulation Performance 2019 And 2020 written by Michael M. Resch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-01 with Computers categories.
This book presents the state of the art in High Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general. The contributions cover a broad range of topics, from performance evaluations in context with power efficiency to Computational Fluid Dynamics and High Performance Data Analytics. In addition, they explore new topics like the use of High Performance Computers in the field of Artificial Intelligence and Machine Learning. All contributions are based on selected papers presented at the 30th Workshop on Sustained Simulation Performance (WSSP) held at the High Performance Computing Center, University of Stuttgart, Germany in October 2019 and on the papers for the planned Workshop on Sustained Simulation Performance in March 2020, which could not take place due to the Covid-19 pandemic.