Learning Representation for Multi-View Data Analysis by Zhengming Ding
This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.
A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.-
Game Theoretic Problems in Network Economics and Mechanism Design Solutions
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Ontological Engineering
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Mining Software Engineering Data for Software Reuse
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R-Trees: Theory and Applications
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Intelligence Management
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Secure Information Management Using Linguistic Threshold Approach
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Hierarchical Feature Selection for Knowledge Discovery
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Developing Multi-Database Mining Applications
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Seriation in Combinatorial and Statistical Data Analysis
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Uncertainty Handling and Quality Assessment in Data Mining
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Knowledge Discovery in Multiple Databases
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Meta-Programming and Model-Driven Meta-Program Development
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Smart Systems for E-Health
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Trends in Interactive Visualization
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Business Intelligence and Performance Management
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Privacy and Anonymity in Information Management Systems
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Scientific Data Analysis using Jython Scripting and Java
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Adaptive Resonance Theory in Social Media Data Clustering
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Agent-Based Service-Oriented Computing
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Knowledge Processing with Interval and Soft Computing
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Data Mining with Computational Intelligence
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Creating Web-based Laboratories
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Data Complexity in Pattern Recognition
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Representation and Management of Narrative Information
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Emergent Web Intelligence: Advanced Information Retrieval
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Machine Learning and Data Mining for Computer Security
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Data Mining for Social Robotics
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Convergence and Knowledge Processing in Multi-Agent Systems
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Artificial Intelligence and Economic Theory: Skynet in the Market
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Advanced Methods for Knowledge Discovery from Complex Data
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Understanding Information
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Robust Representation for Data Analytics
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Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
The book should be well received by advanced postgraduate students and data (especially big data) analystsA background in statistics, mathematics, and computing is a prerequisite for reading. It is surely a must-have reference book for any scientific library. (Soubhik Chakraborty, Computing Reviews, May 07, 2019)
| SKU | Unavailable |
| ISBN 13 | 9783030007331 |
| ISBN 10 | 3030007332 |
| Title | Learning Representation for Multi-View Data Analysis |
| Author | Zhengming Ding |
| Series | Advanced Information And Knowledge Processing |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2018-12-17 |
| Number of pages | 268 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |