Results 31 to 40 of about 1,699,128 (261)
Deep Multi-View Concept Learning [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Multi-view data is common in real-world datasets, where different views describe distinct perspectives. To better summarize the consistent and complementary information in multi-view data, researchers have proposed various multi-view representation learning algorithms, typically based on factorization models. However, most previous methods were focused
Cai Xu +5 more
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Multi-View Classification via a Fast and Effective Multi-View Nearest-Subspace Classifier
IEEE Access, 2019 Multi-view data represented in multiple views contains more complementary information than a single view, whereby multi-view learning explores and utilizes the multi-view data.
Ting Shu, Bob Zhang, Yuan Yan Tang
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Fusing Local and Global Information for One-Step Multi-View Subspace Clustering
Applied Sciences, 2022 Multi-view subspace clustering has drawn significant attention in the pattern recognition and machine learning research community. However, most of the existing multi-view subspace clustering methods are still limited in two aspects.
Yiqiang Duan +3 more
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Multi-View Based Multi-Model Learning for MCI Diagnosis
Brain Sciences, 2020 Mild cognitive impairment (MCI) is the early stage of Alzheimer’s disease (AD). Automatic diagnosis of MCI by magnetic resonance imaging (MRI) images has been the focus of research in recent years. Furthermore, deep learning models based on 2D view
Ping Cao, Jie Gao, Zuping Zhang
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Multi-view constrained clustering with an incomplete mapping between views [PDF]
, 2012 Multi-view learning algorithms typically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. However, many applications provide only a partial mapping between the views, creating a
desJardins, Marie +2 more
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A Novel Adaptive Multi-View Non-Negative Graph Semi-Supervised ELM
IEEE Access, 2020 This paper represents a semi-supervised learning framework, which integrates multi-view learning, extreme learning machine (ELM) and graph-based semi-supervised learning.
Feng Zheng +4 more
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A survey on canonical correlation analysis based multi-view learning
智能科学与技术学报, 2022 Multi-view learning (MVL) is a strategy for fusing data from different sources or subsets.Canonical correlation analysis (CCA) is very important in MVL, whose main idea is to maximize the correlation of different views.The traditional CCA can only ...
Chenfeng GUO, Dongrui WU
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, 2015 In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples. The problem is formulated under the multi-view learning framework and a Consensus-based Multi-View Maximum Entropy Discrimination (CMV-MED ...
Hero III, Alfred O. +2 more
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Exploring Dynamic Hierarchical Fusion for Multi-View Clustering
IEEE AccessMulti-view clustering is effective at uncovering the latent structures within different views or modalities. However, existing approaches often oversimplify the problem by treating the contribution and granularity of information from all views as uniform,
Zhenshan Chen +6 more
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Learning from Multi-View Multi-Way Data via Structural Factorization Machines
, 2018 Real-world relations among entities can often be observed and determined by different perspectives/views. For example, the decision made by a user on whether to adopt an item relies on multiple aspects such as the contextual information of the decision ...
Cao, Bokai +4 more
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