Robust Representation for Data Analytics by Sheng Li
This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary.Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics 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.
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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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Learning Representation for Multi-View Data Analysis
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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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Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
Dr. Yun Fu is a professor at the State University of New York at Buffalo
Dr. Yunqian Ma is a senior principal research scientist of Honeywell Labs at the Honeywell International Inc.
Dr. Yunqian Ma is a senior principal research scientist of Honeywell Labs at the Honeywell International Inc.
| SKU | Unavailable |
| ISBN 13 | 9783319867960 |
| ISBN 10 | 3319867962 |
| Title | Robust Representation for Data Analytics |
| Author | Sheng Li |
| Series | Advanced Information And Knowledge Processing |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2018-08-04 |
| Number of pages | 224 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |