Results 11 to 20 of about 24,671,802 (285)
Biased Incomplete Multi-View Learning
Proceedings of the AAAI Conference on Artificial IntelligenceConsidering the ubiquitous phenomenon of missing views in multi-view data, incomplete multi-view learning is a crucial task in many applications. Existing methods usually follow an impute-then-predict strategy for handling this problem. However, they often assume that the view-missing patterns are uniformly random in multi-view data, which does not ...
Haishun Chen +4 more
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Tensor-Based Uncoupled and Incomplete Multi-View Clustering
MathematicsMulti-view clustering demonstrates strong performance in various real-world applications. However, real-world data often contain incomplete and uncoupled views.
Yapeng Liu +5 more
doaj +2 more sources
Incomplete Multi-View Weak-Label Learning [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Learning from multi-view multi-label data has wide applications. There are two main challenges of this learning task: incomplete views and missing (weak) labels. The former assumes that views may not include all data objects. The weak label setting implies that only a subset of relevant labels are provided for training objects while other labels are ...
Qiaoyu Tan +4 more
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Unsupervised Learning from Multi-view Data [PDF]
, 2016 With the advance of technology, data are often with multiple modalities or coming from multiple sources. Such data are called multi-view data. Usually, multiple views provide complementary information for the semantically same data.
Weixiang Shao (7984739)
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Localized Sparse Incomplete Multi-view Clustering [PDF]
, 2023 Incomplete multi-view clustering, which aims to solve the clustering problem on the incomplete multi-view data with partial view missing, has received more and more attention in recent years.
Xu, Yong +4 more
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, 2023 As we all know, multi-view data is more expressive than single-view data and multi-label annotation enjoys richer supervision information than single-label, which makes multi-view multi-label learning widely applicable for various pattern recognition ...
Xu, Yong +3 more
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Consensus Partition Guided Incomplete Multi-View Clustering
IEEE AccessIncomplete multi-view clustering aims to derive a comprehensive consensus partition that is shared across all views, a topic that has attracted significant attention in recent years.
Chunyu Yang, Hongyun Yue
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An Ensemble Multi-View Federated Learning Intrusion Detection for IoT
IEEE Access, 2021 The rise in popularity of Internet of Things (IoT) devices has attracted hackers to develop IoT-specific attacks. The microservice architecture of IoT devices relies on the Internet to provide their intended services. An unguarded IoT network makes inter-
Dinesh Chowdary Attota +3 more
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MFHE: Multi-View Fusion-Based Heterogeneous Information Network Embedding
Applied Sciences, 2022 Depending on the type of information network, information network embedding is classified into homogeneous information network embedding and heterogeneous information network (HIN) embedding. Compared with the homogeneous network, HIN composition is more
Tingting Liu, Jian Yin, Qingfeng Qin
doaj +1 more source
Incomplete Multi-view Clustering via Diffusion Completion [PDF]
, 2023 Incomplete multi-view clustering is a challenging and non-trivial task to provide effective data analysis for large amounts of unlabeled data in the real world. All incomplete multi-view clustering methods need to address the problem of how to reduce the
Fang, Sifan
core