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Titlebook: Multiview Machine Learning; Shiliang Sun,Liang Mao,Lidan Wu Book 2019 Springer Nature Singapore Pte Ltd. 2019 Multiview Learning.Data Fusi

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发表于 2025-3-21 19:05:59 | 显示全部楼层 |阅读模式
书目名称Multiview Machine Learning
编辑Shiliang Sun,Liang Mao,Lidan Wu
视频video
概述The first comprehensive and in-depth book on multiview machine learning.Blends theory and practice, presenting state-of-the-art methodologies.Equips readers to handle complex data analysis tasks with
图书封面Titlebook: Multiview Machine Learning;  Shiliang Sun,Liang Mao,Lidan Wu Book 2019 Springer Nature Singapore Pte Ltd. 2019 Multiview Learning.Data Fusi
描述.This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains.  .
出版日期Book 2019
关键词Multiview Learning; Data Fusion; Data Integration; Multi-Modal Learning; Machine Learning; Semi-Supervise
版次1
doihttps://doi.org/10.1007/978-981-13-3029-2
isbn_ebook978-981-13-3029-2
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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s.Equips readers to handle complex data analysis tasks with .This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This
发表于 2025-3-22 07:13:48 | 显示全部楼层
Book 2019data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains.  .
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https://doi.org/10.1007/978-981-13-3029-2Multiview Learning; Data Fusion; Data Integration; Multi-Modal Learning; Machine Learning; Semi-Supervise
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Springer Nature Singapore Pte Ltd. 2019
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