Results 241 to 250 of about 690,102 (265)

Double‐Tucker Decomposition and Its Computations

Numerical Linear Algebra with Applications
ABSTRACTThe famous Tucker decomposition has been widely and successfully used in many fields. However, it often suffers from the curse of dimensionality due to the core tensor and large ranks. To tackle this issue, we introduce an additional core tensor into Tucker decomposition and propose the so‐called double‐Tucker (dTucker) decomposition.
Mengyu Wang, Honghua Cui, Hanyu Li
openaire   +1 more source

Wafer Pattern Recognition Using Tucker Decomposition

2019 IEEE 37th VLSI Test Symposium (VTS), 2019
In production test data analytics, it is often that an analysis involves the recognition of a conceptual pattern on a wafer map. A wafer pattern may hint a particular issue in the production by itself or guide the analysis into a certain direction. In this work, we introduce a novel approach to recognize patterns on a wafer map of pass/fail locations ...
Ahmed Wahba, Li-C. Wang, Zheng Zhang 0005, Nik Sumikawa   +3 more
openaire   +2 more sources

Supervised Nonnegative Tucker Decomposition for Computational Phenotyping

2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2019
With the availability of Electronic Health Records (EHR) data, lots of predictive tasks in medical practice seem solvable by building predictive models. However, EHR data always contains various medical concepts (e.g., diagnosis, medicines, lab tests) with high dimensions and mass correlations among them.
Kai Yang, Wenqi Sun, Junfeng Zhao 0001, Yasha Wang, Bing Xie   +4 more
openaire   +1 more source

Quality assessment for color images with tucker decomposition

2012 19th IEEE International Conference on Image Processing, 2012
As an extension of the singular value decomposition based approaches, a novel metric based on Tucker decomposition for color image quality assessment is proposed in this paper. It extracts both the spacial and chromatic information of a color image with Tucker decomposition.
Cheng Cheng, Hanli Wang
openaire   +1 more source

Local Learning Rules for Nonnegative Tucker Decomposition

2009
Analysis of data with high dimensionality in modern applications, such as spectral analysis, neuroscience, chemometrices naturally requires tensorial approaches different from standard matrix factorizations (PCA, ICA, NMF). The Tucker decomposition and its constrained versions with sparsity and/or nonnegativity constraints allow for the extraction of ...
Anh Huy Phan 0001, Andrzej Cichocki
openaire   +1 more source

Sparse Symmetric Format for Tucker Decomposition

IEEE Transactions on Parallel and Distributed Systems, 2023
Shruti Shivakumar, Jiajia Li 0001, Ramakrishnan Kannan, Srinivas Aluru   +3 more
openaire   +2 more sources

Accurate Regularized Tucker Decomposition for Image Restoration

Applied Mathematical Modelling, 2023
Zhejun Huang, Wenwu Gong
exaly  

The Correlation-Based Tucker Decomposition for Hyperspectral Image Compression

Neurocomputing, 2021
Zhibin Pan
exaly  

Dynamic L1-Norm Tucker Tensor Decomposition

IEEE Journal on Selected Topics in Signal Processing, 2021
Mayur Dhanaraj, Panagiotis Panos P. Markopoulos, Ashley Prater-Bennette   +2 more
exaly  

Privacy-Preserving Tucker Train Decomposition Over Blockchain-Based Encrypted Industrial IoT Data

IEEE Transactions on Industrial Informatics, 2021
Jun Feng, Laurence T. Yang, Benard Gavuna   +2 more
exaly