Intelligent Data Engineering And Automated Learning Ideal 2016
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Author |
: Hujun Yin |
Publisher |
: Springer |
Total Pages |
: 664 |
Release |
: 2016-09-12 |
ISBN-10 |
: 9783319462578 |
ISBN-13 |
: 3319462571 |
Rating |
: 4/5 (78 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2016 by : Hujun Yin
This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis.
Author |
: Hujun Yin |
Publisher |
: Springer |
Total Pages |
: 364 |
Release |
: 2018-11-08 |
ISBN-10 |
: 9783030034962 |
ISBN-13 |
: 3030034968 |
Rating |
: 4/5 (62 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2018 by : Hujun Yin
This two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
Author |
: Cesar Analide |
Publisher |
: Springer Nature |
Total Pages |
: 424 |
Release |
: 2020-10-29 |
ISBN-10 |
: 9783030623623 |
ISBN-13 |
: 3030623629 |
Rating |
: 4/5 (23 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2020 by : Cesar Analide
This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.
Author |
: Hujun Yin |
Publisher |
: Springer Nature |
Total Pages |
: 564 |
Release |
: 2022-11-20 |
ISBN-10 |
: 9783031217531 |
ISBN-13 |
: 3031217535 |
Rating |
: 4/5 (31 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2022 by : Hujun Yin
This book constitutes the refereed proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022, which took place in Manchester, UK, during November 24-26, 2022. The 52 full papers included in this book were carefully reviewed and selected from 79 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.
Author |
: Hujun Yin |
Publisher |
: Springer Nature |
Total Pages |
: 575 |
Release |
: 2019-11-07 |
ISBN-10 |
: 9783030336073 |
ISBN-13 |
: 3030336077 |
Rating |
: 4/5 (73 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2019 by : Hujun Yin
This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.
Author |
: Hujun Yin |
Publisher |
: Springer |
Total Pages |
: 626 |
Release |
: 2017-10-23 |
ISBN-10 |
: 9783319689357 |
ISBN-13 |
: 3319689355 |
Rating |
: 4/5 (57 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2017 by : Hujun Yin
This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017. The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
Author |
: Hujun Yin |
Publisher |
: Springer Nature |
Total Pages |
: 663 |
Release |
: 2021-11-23 |
ISBN-10 |
: 9783030916084 |
ISBN-13 |
: 3030916081 |
Rating |
: 4/5 (84 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2021 by : Hujun Yin
This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.
Author |
: Paulo Quaresma |
Publisher |
: Springer Nature |
Total Pages |
: 561 |
Release |
: 2023-12-16 |
ISBN-10 |
: 9783031482328 |
ISBN-13 |
: 3031482328 |
Rating |
: 4/5 (28 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2023 by : Paulo Quaresma
This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.
Author |
: |
Publisher |
: |
Total Pages |
: 882 |
Release |
: 2004 |
ISBN-10 |
: UOM:39015058295968 |
ISBN-13 |
: |
Rating |
: 4/5 (68 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning by :
Author |
: Cesar Analide |
Publisher |
: Springer Nature |
Total Pages |
: 633 |
Release |
: 2020-10-29 |
ISBN-10 |
: 9783030623654 |
ISBN-13 |
: 3030623653 |
Rating |
: 4/5 (54 Downloads) |
Synopsis Intelligent Data Engineering and Automated Learning – IDEAL 2020 by : Cesar Analide
This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.