Results 21 to 30 of about 223,331 (198)
Implicit Regularization in Tensor Factorization
CoRR, 2021 Recent efforts to unravel the mystery of implicit regularization in deep learning have led to a theoretical focus on matrix factorization -- matrix completion via linear neural network. As a step further towards practical deep learning, we provide the first theoretical analysis of implicit regularization in tensor factorization -- tensor completion via
Noam Razin, Asaf Maman, Nadav Cohen 0001
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IEEE Access, 2020 Fault diagnosis technology is crucial to ensure the long-term reliability of the industrial process control system. With the increase of industrial data availability, conventional monitoring approaches may not function well under the assumption that the ...
Lin Luo, Lei Xie, Hongye Su
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N Dimensional Tensor Decomposition Recommendation Algorithm Based on User’s Neighbors [PDF]
Jisuanji gongcheng, 2017 Recommendation algorithm based on tensor factorization has low accuracy and data sparseness problem.Therefore,on the basic of the traditional tensor decomposition model,this paper introduces the user nearest neighbor information,and proposes N ...
CHEN Jianmei,SUN Yajun
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Stack Operation of Tensor Networks
Frontiers in Physics, 2022 The tensor network, as a factorization of tensors, aims at performing the operations that are common for normal tensors, such as addition, contraction, and stacking.
Tianning Zhang +4 more
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Boolean Tensor Factorizations [PDF]
2011 IEEE 11th International Conference on Data Mining, 2011 Tensors are multi-way generalizations of matrices, and similarly to matrices, they can also be factorized, that is, represented (approximately) as a product of factors. These factors are typically either all matrices or a mixture of matrices and tensors.
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Decoupling braided tensor factors [PDF]
Physics of Atomic Nuclei, 2001 We briefly report on our result that the braided tensor product algebra of two module algebras $A_1,A_2$ of a quasitriangular Hopf algebra $H$ is equal to the ordinary tensor product algebra of $H_1$ with a subalgebra isomorphic to $A_2$ and commuting with $A_1$, provided there exists a realization of $H$ within $A_1$. As applications of the theorem we
FIORE, GAETANO, H. STEINHACKER, J. WESS
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On Tensors, Sparsity, and Nonnegative Factorizations [PDF]
SIAM Journal on Matrix Analysis and Applications, 2012 Tensors have found application in a variety of fields, ranging from chemometrics to signal processing and beyond. In this paper, we consider the problem of multilinear modeling of sparse count data. Our goal is to develop a descriptive tensor factorization model of such data, along with appropriate algorithms and theory.
Eric C. Chi, Tamara G. Kolda
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Shape-Adaptive Tensor Factorization Model for Dimensionality Reduction of Hyperspectral Images
IEEE Access, 2019 Tensor-based dimensionality reduction (DR) of hyperspectral images is a promising research topic. However, patch-based tensorization usually adopts a squared neighborhood with fixed window size, which may be inaccurate in modeling the local spatial ...
Zhaohui Xue, Sirui Yang, Mengxue Zhang
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A Biased Deep Tensor Factorization Network For Tensor Completion
CoRR, 2021 Tensor decomposition is a popular technique for tensor completion, However most of the existing methods are based on linear or shallow model, when the data tensor becomes large and the observation data is very small, it is prone to over fitting and the performance decreases significantly.
Qianxi Wu, An-Bao Xu
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