Towards Integrative Machine Learning And Knowledge Extraction

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Towards Integrative Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Randy Goebel,Massimo Ferri,Vasile Palade
Publisher : Springer
Page : 207 pages
File Size : 47,9 Mb
Release : 2017-10-27
Category : Computers
ISBN : 9783319697758

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Towards Integrative Machine Learning and Knowledge Extraction by Andreas Holzinger,Randy Goebel,Massimo Ferri,Vasile Palade Pdf

The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,Federico Cabitza,Andrea Campagner,A Min Tjoa,Edgar Weippl
Publisher : Springer Nature
Page : 335 pages
File Size : 45,8 Mb
Release : 2023-08-21
Category : Computers
ISBN : 9783031408373

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,Federico Cabitza,Andrea Campagner,A Min Tjoa,Edgar Weippl Pdf

This volume LNCS-IFIP constitutes the refereed proceedings of the 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023 in Benevento, Italy, during August 28 – September 1, 2023. The 18 full papers presented together were carefully reviewed and selected from 30 submissions. The conference focuses on integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer Nature
Page : 390 pages
File Size : 44,5 Mb
Release : 2022-08-10
Category : Computers
ISBN : 9783031144639

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022. The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer
Page : 379 pages
File Size : 47,9 Mb
Release : 2018-08-23
Category : Computers
ISBN : 9783319997407

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer Nature
Page : 428 pages
File Size : 48,9 Mb
Release : 2019-08-22
Category : Computers
ISBN : 9783030297268

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl
Publisher : Springer
Page : 383 pages
File Size : 48,5 Mb
Release : 2017-08-23
Category : Computers
ISBN : 9783319668086

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar R. Weippl
Publisher : Unknown
Page : 0 pages
File Size : 40,9 Mb
Release : 2022
Category : Knowledge management
ISBN : 8303114468

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A Min Tjoa,Edgar R. Weippl Pdf

This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022. The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A. Min Tjoa,Edgar R. Weippl
Publisher : Unknown
Page : 372 pages
File Size : 51,6 Mb
Release : 2018
Category : Data mining
ISBN : 3319997416

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A. Min Tjoa,Edgar R. Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.

Artificial Intelligence and Machine Learning for Digital Pathology

Author : Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller
Publisher : Springer Nature
Page : 351 pages
File Size : 40,8 Mb
Release : 2020-06-24
Category : Computers
ISBN : 9783030504021

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Artificial Intelligence and Machine Learning for Digital Pathology by Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller Pdf

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

Humanity Driven AI

Author : Fang Chen,Jianlong Zhou
Publisher : Springer Nature
Page : 330 pages
File Size : 40,9 Mb
Release : 2021-12-01
Category : Computers
ISBN : 9783030721886

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Humanity Driven AI by Fang Chen,Jianlong Zhou Pdf

Artificial Intelligence (AI) is changing the world around us, and it is changing the way people are living, working, and entertaining. As a result, demands for understanding how AI functions to achieve and enhance human goals from basic needs to high level well-being (whilst maintaining human health) are increasing. This edited book systematically investigates how AI facilitates enhancing human needs in the digital age, and reports on the state-of-the-art advances in theories, techniques, and applications of humanity driven AI. Consisting of five parts, it covers the fundamentals of AI and humanity, AI for productivity, AI for well-being, AI for sustainability, and human-AI partnership. Humanity Driven AI creates an important opportunity to not only promote AI techniques from a humanity perspective, but also to invent novel AI applications to benefit humanity. It aims to serve as the dedicated source for the theories, methodologies, and applications on humanity driven AI, establishing state-of-the-art research, and providing a ground-breaking book for graduate students, research professionals, and AI practitioners.

Machine Learning and Knowledge Extraction

Author : Andreas Holzinger,Peter Kieseberg,A. Min Tjoa,Edgar R. Weippl
Publisher : Unknown
Page : 128 pages
File Size : 50,7 Mb
Release : 2019
Category : Data mining
ISBN : 3030297276

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Machine Learning and Knowledge Extraction by Andreas Holzinger,Peter Kieseberg,A. Min Tjoa,Edgar R. Weippl Pdf

This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

AI Applications to Communications and Information Technologies

Author : Daniel Minoli,Benedict Occhiogrosso
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 44,9 Mb
Release : 2023-11-08
Category : Technology & Engineering
ISBN : 9781394190010

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AI Applications to Communications and Information Technologies by Daniel Minoli,Benedict Occhiogrosso Pdf

AI Applications to Communications and Information Technologies Apply the technology of the future to networking and communications. Artificial intelligence, which enables computers or computer-controlled systems to perform tasks which ordinarily require human-like intelligence and decision-making, has revolutionized computing and digital industries like few other developments in recent history. Tools like artificial neural networks, large language models, and deep learning have quickly become integral aspects of modern life. With research and development into AI technologies proceeding at lightning speeds, the potential applications of these new technologies are all but limitless. AI Applications to Communications and Information Technologies offers a cutting-edge introduction to AI applications in one particular set of disciplines. Beginning with an overview of foundational concepts in AI, it then moves through numerous possible extensions of this technology into networking and telecommunications. The result is an essential introduction for researchers and for technology undergrad/grad student alike. AI Applications to Communications and Information Technologies readers will also find: In-depth analysis of both current and evolving applications Detailed discussion of topics including generative AI, chatbots, automatic speech recognition, image classification and recognition, IoT, smart buildings, network management, network security, and more An authorial team with immense experience in both research and industry AI Applications to Communications and Information Technologies is ideal for researchers, industry observers, investors, and advanced students of network communications and related fields.

Machine Learning and Big Data Analytics

Author : Rajiv Misra,Rana Omer,Muttukrishnan Rajarajan,Bharadwaj Veeravalli,Nishtha Kesswani,Priyanka Mishra
Publisher : Springer Nature
Page : 552 pages
File Size : 46,6 Mb
Release : 2023-06-06
Category : Mathematics
ISBN : 9783031151750

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Machine Learning and Big Data Analytics by Rajiv Misra,Rana Omer,Muttukrishnan Rajarajan,Bharadwaj Veeravalli,Nishtha Kesswani,Priyanka Mishra Pdf

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

Advances in Machine Learning and Data Science

Author : Damodar Reddy Edla,Pawan Lingras,Venkatanareshbabu K.
Publisher : Springer
Page : 380 pages
File Size : 49,6 Mb
Release : 2018-05-16
Category : Technology & Engineering
ISBN : 9789811085697

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Advances in Machine Learning and Data Science by Damodar Reddy Edla,Pawan Lingras,Venkatanareshbabu K. Pdf

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.

AI*IA 2018 – Advances in Artificial Intelligence

Author : Chiara Ghidini,Bernardo Magnini,Andrea Passerini,Paolo Traverso
Publisher : Springer
Page : 566 pages
File Size : 41,8 Mb
Release : 2018-11-08
Category : Computers
ISBN : 9783030038403

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AI*IA 2018 – Advances in Artificial Intelligence by Chiara Ghidini,Bernardo Magnini,Andrea Passerini,Paolo Traverso Pdf

This book constitutes the refereed proceedings of the XVIIth International Conference of the Italian Association for Artificial Intelligence, AI*IA 2018, held in Trento, Italy, in November 2018. The 41 full papers were carefully reviewed and selected from 67 submissions. The papers have been organized in the following topical sections: Agents and Multi-Agent Systems; Applications of AI; Knowledge Engineering, Ontologies and the Semantic Web; Knowledge Representation and Reasoning; Machine Learning; Natural Language Processing; Planning and Scheduling; and Recommendation Systems and Decision Making.