Results 21 to 30 of about 690,102 (265)
Reconstruction Optimization Algorithm of 3D Temperature Distribution Based on Tucker Decomposition
Applied Sciences, 2022 For the purpose of solving the large temperature field reconstruction error caused by different measuring point arrangements and the problem that the prior dataset cannot be built due to data loss or distortion in actual measurement, a three-dimensional ...
Zhaoyu Liu +3 more
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The detection algorithm based on low rank tensor decomposition of large-scale MIMO
上海师范大学学报. 自然科学版, 2017 In this paper,we propose an improved Tucker decomposition algorithm.The tensor is decomposed into two dimensions.By using matrix rank reduction and convergence in both Tucker and improved Tucker algorithm,we get an approximate estimation which can ...
Liu Xingyue +3 more
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Discovering facts with boolean tensor tucker decomposition [PDF]
Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013 Open Information Extraction (Open IE) has gained increasing research interest in recent years. The first step in Open IE is to extract raw subject--predicate--object triples from the data. These raw triples are rarely usable per se, and need additional post-processing.
Dóra Erdös, Pauli Miettinen
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Remote Sensing, 2022 To excavate adequately the rich information contained in multisource remote sensing data, feature extraction as basic yet important research has two typical applications: one of which is to extract complementary information of multisource data to improve
Tong Gao, Hao Chen, Junhong Lu
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A Two-Stage Framework for Directed Hypergraph Link Prediction
Mathematics, 2022 Hypergraphs, as a special type of graph, can be leveraged to better model relationships among multiple entities. In this article, we focus on the task of hyperlink prediction in directed hypergraphs, which finds a wide spectrum of applications in ...
Guanchen Xiao +4 more
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On Optimizing Distributed Tucker Decomposition for Dense Tensors [PDF]
2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017 The Tucker decomposition expresses a given tensor as the product of a small core tensor and a set of factor matrices. Apart from providing data compression, the construction is useful in performing analysis such as principal component analysis (PCA)and finds applications in diverse domains such as signal processing, computer vision and text analytics ...
Venkatesan T. Chakaravarthy +6 more
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Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness [PDF]
IEEE Transactions on Image Processing, 2015 appears in IEEE Transactions on Image Processing ...
Guoxu Zhou +3 more
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Tucker decomposition-based temporal knowledge graph completion [PDF]
Knowledge-Based Systems, 2022 Knowledge graphs have been demonstrated to be an effective tool for numerous intelligent applications. However, a large amount of valuable knowledge still exists implicitly in the knowledge graphs. To enrich the existing knowledge graphs, recent years witness that many algorithms for link prediction and knowledge graphs embedding have been designed to ...
Pengpeng Shao +5 more
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Measurement Science Review, 2020 Analysis of changes in the brain neural electrical activity measured by the electroencephalogram (EEG) plays a crucial role in the area of brain disorder diagnostics. The elementary latent sources of the brain neural activity can be extracted by a tensor
Rošt’áková Zuzana +3 more
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Hyperspectral image, video compression using sparse tucker tensor decomposition
IET Image Processing, 2021 Hyperspectral image and videos provide rich spectral information content, which facilitates accurate classification, unmixing, temporal change detection, and so on.
Samiran Das
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