Results 31 to 40 of about 1,029,862 (299)
Multi-View Multi-Label Learning With View-Label-Specific Features
IEEE Access, 2019 In multi-view multi-label learning, each object is represented by multiple data views, and belongs to multiple class labels simultaneously. Generally, all the data views have a contribution to the multi-label learning task, but their contributions are ...
Jun Huang +5 more
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Learning in multi-agent systems [PDF]
, 2001 In recent years, multi-agent systems (MASs) have received increasing attention in the artificial intelligence community. Research in multi-agent systems involves the investigation of autonomous, rational and flexible behaviour of entities such as ...
Alonso, E. +14 more
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Environmental capability development in a multi-stakeholder network setting: dynamic learning through multi-stakeholder interactions [PDF]
, 2022 The study offers a nuanced view of multi-stakeholder networks (MSNs) as settings for capability development through learning. Unlike numerous studies of capability development in networks being framed through a resource-based perspective, the study ...
Polina Baranova, Baranova, P.
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Incremental multi‐view correlated feature learning based on non‐negative matrix factorisation
IET Computer Vision, 2021 In real‐world applications, large amounts of data from multiple sources come in the form of streams. This makes multi‐view feature learning cost much time when new instances rise incrementally.
Liang Zhao +3 more
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Unsupervised Multi-view Learning [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Unsupervised multi-view learning is a hot research topic. The main challenge lies in how to integrate information from different views to enhance the unsupervised learning performance. In this paper, we present our research works on multi-view data clustering and multi-view network community detection respectively. The main contributions are summarized
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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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Low‐rank constrained weighted discriminative regression for multi‐view feature learning
CAAI Transactions on Intelligence Technology, 2021 In recent years, multi‐view learning has attracted much attention in the fields of data mining, knowledge discovery and machine learning, and been widely used in classification, clustering and information retrieval, and so forth. A new supervised feature
Chao Zhang, Huaxiong Li
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Trusted Multi-View Deep Learning with Opinion Aggregation [PDF]
, 2022 Multi-view deep learning is performed based on the deep fusion of data from multiple sources, i.e. data with multiple views. However, due to the property differences and inconsistency of data sources, the deep learning results based on the fusion of ...
Liu, Wei +3 more
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A review of multi-instance learning assumptions [PDF]
, 2010 Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature vector.
Frank, Eibe, Foulds, James Richard
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