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10 Result(s)
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Ziang **e
Computer Science
Artificial Intelligence
Big Data
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Book
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Chapter
Introduction
In this chapter, we first give the background for writing this monograph. Then, we provide a formal definition of multiview machine learning and discuss its difference and similarities with related concepts da...
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Chapter
View Construction
In most real applications, data are represented by a single view, which is difficult to apply in multiview learning. In this Chapter, we introduce six view construction methods to generate new views from the o...
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Chapter
Multiview Semi-supervised Learning
Semi-supervised learning is concerned with such learning scenarios where only a small portion of training data are labeled. In multiview settings, unlabeled data can be used to regularize the prediction functi...
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Chapter
Multiview Supervised Learning
Multiview supervised learning algorithm can exploit the multiview nature of the data by the consensus of the views, that is, to seek predictors from different views that agree on the same example. In this chap...
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Chapter
Multiview Active Learning
Active learning is proposed based on the fact that manually labeled examples are expensive, thus it picks the most informative points to label so as to improve the learning efficiency. Combined with multiview ...
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Chapter
Multiview Deep Learning
The multiview deep learning described in this chapter deals with multiview data or simulates constructing its intrinsic structure by using deep learning methods. We highlight three major categories of multivie...
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Chapter
Multiview Subspace Learning
In multiview settings, observations from different views are assumed to share the same subspace. The abundance of views can be utilized to better explore the subspace. In this chapter, we consider two differen...
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Chapter
Multiview Clustering
This chapter introduces three kinds of multiview clustering methods. We begin with the multiview spectral clustering, where the clustering is carried out through the partition of a relationship graph of the da...
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Chapter
Multiview Transfer Learning and Multitask Learning
Transfer learning is proposed to transfer the learned knowledge from source domains to target domains where the target ones own fewer training data. Multitask learning learns multiple tasks simultaneously and ...
