Explainability of the COVID-19 epidemiological model with nonnegative tensor factorization. [PDF]
Int J Data Sci Anal, 2023 The world is witnessing the devastating effects of the COVID-19 pandemic. Each country responded to contain the spread of the virus in the early stages through diverse response measures.
Balasubramaniam T +3 more
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Single-trial decoding of bistable perception based on sparse nonnegative tensor decomposition. [PDF]
Comput Intell Neurosci, 2008 The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual ...
Wang Z, Maier A, Logothetis NK, Liang H.
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Generalized discriminant orthogonal nonnegative tensor factorization for facial expression recognition. [PDF]
ScientificWorldJournal, 2014 In order to overcome the limitation of traditional nonnegative factorization algorithms, the paper presents a generalized discriminant orthogonal non-negative tensor factorization algorithm.
XiuJun Z, Chang L.
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Nonlocal Low-Rank Nonnegative Tensor Factorization for Hyperspectral Unmixing
, 2020 Hyperspectral unmixing decomposes hyperspectral images (HSI) into a collection of constituent materials or end-members and their fractions, i.e., abundances. Nonnegative tensor factorization (NTF) has been utilized thanks to its ability of preserving all
Jun Zhou +9 more
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Non-negative tensor factorization with applications to statistics and computer vision [PDF]
, 2005 We derive algorithms for finding a nonnegative n-dimensional tensor factorization (n-NTF) which includes the non-negative matrix factorization (NMF) as a particular case when n = 2.
Amnon Shashua, Tamir Hazan
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Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing
, 2018 Hyperspectral unmixing aims at decomposing a hyperspectral image (HSI) into a number of constituted materials and associated proportions. Recently, nonnegative tensor factorization (NTF) based methods have been proved effective and natural for ...
Jingzhou Chen +7 more
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Sparse image coding using a 3D non-negative tensor factorization [PDF]
, 2005 We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the past such a decomposition was obtained using nonnegative matrix factorization (
Simon Polak +5 more
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, 2018 International audienceIn this work we present a novel algorithm for nonnegative tensor factorization (NTF). Standard NTF algorithms are very restricted in the size of tensors that can be decomposed.
Vigneron, Vincent +9 more
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Nonnegative tensor factorization for continuous EEG classification
, 2019 In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classify multiple mental tasks.
Cichocki, A, Lee, H, Choi, S, Kim, YD
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A proximal ANLS algorithm for nonnegative tensor factorization with a periodic enhanced line search [PDF]
, 1999 summary:The Alternating Nonnegative Least Squares (ANLS) method is commonly used for solving nonnegative tensor factorization problems. In this paper, we focus on algorithmic improvement of this method.
Bunker, Douglas +3 more
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