Results 51 to 60 of about 169,617 (164)
Multi-view Graph Representation Learning Beyond Homophily
ACM Transactions on Knowledge Discovery from Data, 2023 Unsupervised graph representation learning (GRL) aims at distilling diverse graph information into task-agnostic embeddings without label supervision. Due to a lack of support from labels, recent representation learning methods usually adopt self-supervised learning, and embeddings are learned by solving a handcrafted auxiliary task (so-called pretext ...
Bei Lin +4 more
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Variational Distillation for Multi-View Learning
IEEE Transactions on Pattern Analysis and Machine IntelligenceInformation Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions. However, its great success is generally attributed to estimate the multivariate mutual information which is intractable when the network becomes complicated.
Xudong Tian +8 more
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PAC-Bayes analysis of multi-view learning [PDF]
Information Fusion, 2017 This paper presents eight PAC-Bayes bounds to analyze the generalization performance of multi-view classifiers. These bounds adopt data dependent Gaussian priors which emphasize classifiers with high view agreements. The center of the prior for the first two bounds is the origin, while the center of the prior for the third and fourth bounds is given by
Sun, S, Shawe-Taylor, J, Mao, L
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Multi-View Network Representation Learning Algorithm Research
Algorithms, 2019 Network representation learning is a key research field in network data mining. In this paper, we propose a novel multi-view network representation algorithm (MVNR), which embeds multi-scale relations of network vertices into the low dimensional ...
Zhonglin Ye +3 more
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One-step Multi-view Clustering Based on Diversity and Consistency [PDF]
Jisuanji gongchengWith the development of data collection technology, multi-view data have become increasingly common. Compared to single-view data, multi-view data contain richer information, which is usually characterized by consistency and diversity information.
HU Aoran, CHEN Xiaohong
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Multi-view Clustering: A Survey
Big Data Mining and Analytics, 2018 In the big data era, the data are generated from different sources or observed from different views. These data are referred to as multi-view data. Unleashing the power of knowledge in multi-view data is very important in big data mining and analysis ...
Yan Yang, Hao Wang
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Multi-Way, Multi-View Learning
, 2009 9 pages, 4 ...
Huopaniemi, Ilkka +4 more
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Multi-View Learning With Robust Generalized Eigenvalue Proximal SVM
IEEE Access, 2019 Multi-view learning mechanism, which enhances learning performance by training multi-model data sets, is a popular filed in recent years. Multi-view generalized eigenvalue proximal support vector machine (MvGSVM), as a most recently proposed classifier ...
Peng Huang +4 more
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Multi-view Discriminative Sequential Learning [PDF]
, 2005 Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other tasks of discrimination. However, semi-supervised learning mechanisms that utilize inexpensive unlabeled sequences in addition to few labeled sequences – such as the Baum-Welch ...
Ulf Brefeld +2 more
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A Feature-Reduction Multi-View k-Means Clustering Algorithm
IEEE Access, 2019 The k-means clustering algorithm is the oldest and most known method in cluster analysis. It has been widely studied with various extensions and applied in a variety of substantive areas.
Miin-Shen Yang, Kristina P. Sinaga
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