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Tensor decompositions, such as CANDECOMP/PARAFAC (CP), are widely used in a variety of applications, such as chemometrics, signal processing, and machine learning.
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Practical aspects of PARAFAC modeling of fluorescence excitation-emission data
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PARAFAC and missing values
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Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone
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Nonlocal Coupled Tensor CP Decomposition for Hyperspectral and Multispectral Image Fusion
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Fluorescence spectroscopy as a potential metabonomic tool for early detection of colorectal cancer
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Canonical polyadic decomposition with a columnwise orthonormal factor matrix
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Fluorescence spectroscopy and multi-way techniques. PARAFAC
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Fast alternating LS algorithms for high order CANDECOMP/PARAFAC tensor factorizations
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Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations
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Tensor Decomposition for Signal Processing and Machine Learning
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TTC: A high-performance Compiler for Tensor Transpositions
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A practical randomized CP tensor decomposition
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Coherence constrained alternating least squares. In 2018 26th European Signal Processing Conference (EUSIPCO) . 613–617
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Liyang Hao, Siqi Liang, Jinmian Ye, and Zenglin Xu. 2018 · 2018
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Cyclops Tensor Framework: Reducing Communication and Eliminating Load Imbalance in Massively Parallel Contractions. In 2013 IEEE 27th International Symposium on Parallel and Distributed Processing . 813–824
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Three-Way Component Analysis Using the R Package ThreeWay
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Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations
S. Hansen, T. Plantenga, and T.G. Kolda. 2015 · 2015
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ParCube: Sparse Parallelizable CANDECOMP-PARAFAC Tensor Decomposition
Evangelos E. Papalexakis, Christos Faloutsos, and Nicholas D. Sidiropoulos. 2015 · 2015
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Elmar Peise, Diego Fabregat-Traver, and Paolo Bientinesi. 2015 · 2015
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SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication. In 2015 IEEE International Parallel and Distributed Processing Symposium . 61–70
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SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication. In 2015 IEEE International Parallel and Distributed Processing Symposium . 61–70
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Shared-Memory Parallelization of MTTKRP for Dense Tensors. In Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (Vienna, Austria) (PPoPP ’18) . Association for Computing Machinery, New York, NY, USA, 393–394
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Alternating Optimization for Tensor Factorization with Orthogonality Constraints: Algorithm and Parallel Implementation. In 2018 International Conference on High Performance Computing & Simulation (HPCS) . IEEE, 439–444
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MATLAB Tensor Toolbox Version 3.1
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Accelerating alternating least squares for tensor decomposition by pairwise perturbation
L. Ma and E. Solomonik. 2019 · 2019
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Software for Sparse Tensor Decomposition on Emerging Computing Architectures
Eric T. Phipps and Tamara G. Kolda. 2019 · 2019
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Extrapolated alternating algorithms for approximate canonical polyadic decomposition. In ICASSP 2020 – 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 3147–3151
A.M.S. Ang, J.E. Cohen, L.T.K. Hien, and N. Gillis. 2019 · 2020
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The N-way Toolbox
R. Bro. 2020 · 2020
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Intel® Math Kernel Library documentation
Intel Corporation. 2020 · 2020
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NVIDIA, Péter Vingelmann, and Frank H.P. Fitzek. 2020 · 2020
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PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints
Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A Matheson, and Haesun Park. 2021 · 2021
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The landscape of software for tensor computations
Christos Psarras, Lars Karlsson, Jiajia Li, and Paolo Bientinesi. 2021 · 2021
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