Results 31 to 40 of about 690,102 (265)
On Optimizing Distributed Tucker Decomposition for Sparse Tensors [PDF]
Proceedings of the 2018 International Conference on Supercomputing, 2018 The Tucker decomposition generalizes the notion of Singular Value Decomposition (SVD) to tensors, the higher dimensional analogues of matrices. We study the problem of constructing the Tucker decomposition of sparse tensors on distributed memory systems via the HOOI procedure, a popular iterative method.
Venkatesan T. Chakaravarthy +6 more
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EURASIP Journal on Advances in Signal Processing, 2023 Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar is an emerging technology to offer range-angle-dependent beampattern. Polarimetric FDA-MIMO radar can sense additional polarization information to improve target identification ...
Qi Zhang, Hong Jiang, Yunchang Liu
doaj +1 more source
Some Theory on Non-negative Tucker Decomposition [PDF]
, 2017 Some theoretical difficulties that arise from dimensionality reduction for tensors with non-negative coefficients is discussed in this paper. A necessary and sufficient condition is derived for a low non-negative rank tensor to admit a non-negative Tucker decomposition with a core of the same non-negative rank.
Cohen, Jeremy +2 more
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Nonnegative Tensor Completion via Low-Rank Tucker Decomposition: Model and Algorithm
IEEE Access, 2019 We consider the problem of low-rank tensor decomposition of incomplete tensors that has applications in many data analysis problems, such as recommender systems, signal processing, machine learning, and image inpainting.
Bilian Chen +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Change detection from multitemporal hyperspectral images has attracted great attention. Most traditional methods using spectral information for change detection treat a hyperspectral image as a two-dimensional matrix and do not take into account ...
Zengfu Hou, Wei Li, Ran Tao, Qian Du
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IEEE Access, 2019 In order to deal with the problem of massive historical multi-station SCADA data storage in distribution management system, this paper proposes a data compression method for power distribution system based on tensor Tucker decomposition.
Hongshan Zhao +3 more
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Remote Sensing Imagery Object Detection Model Compression via Tucker Decomposition
Mathematics, 2023 Although convolutional neural networks (CNNs) have made significant progress, their deployment onboard is still challenging because of their complexity and high processing cost.
Lang Huyan +10 more
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Randomized Algorithms for Computation of Tucker Decomposition and Higher Order SVD (HOSVD)
IEEE Access, 2021 Big data analysis has become a crucial part of new emerging technologies such as the internet of things, cyber-physical analysis, deep learning, anomaly detection, etc.
Salman Ahmadi-Asl +6 more
doaj +1 more source
Incremental Hierarchical Tucker Decomposition
CoRRWe present two new algorithms for approximating and updating the hierarchical Tucker decomposition of tensor streams. The first algorithm, Batch Hierarchical Tucker - leaf to root (BHT-l2r), proposes an alternative and more efficient way of approximating a batch of similar tensors in hierarchical Tucker format. The second algorithm, Hierarchical Tucker
Doruk Aksoy, Alex A. Gorodetsky
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Arthritis Care &Research, Accepted Article.Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck +10 more
wiley +1 more source