Results 41 to 50 of about 1,630,238 (295)
Robust Probabilistic Matrix Tri-factorization
Jisuanji kexue yu tansuo, 2020 Matrix factorization is a commonly-used data analysis tool in computer vision, machine learning and data mining. In recent years, the probabilistic models of matrix factorization have become the focus of attention.
SHI Jiarong, CHEN Jiaojiao
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Collaborative Filtering Recommendation Algorithm Based on Semi-Autoencoder [PDF]
Jisuanji gongcheng, 2021 To effectively use the user-item interaction history and auxiliary information in recommendation systems,this paper proposes an improved collaborative filtering recommendation algorithm.Based on semi-autoencoder,the features of auxiliary information of ...
ZHANG Haobo, XUE Feng, LIU Kai
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CoRR, 2020 Constrained low-rank matrix approximations have been known for decades as powerful linear dimensionality reduction techniques to be able to extract the information contained in large data sets in a relevant way. However, such low-rank approaches are unable to mine complex, interleaved features that underlie hierarchical semantics. Recently, deep matrix
Pierre De Handschutter +2 more
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Fredholm factorization of Wiener-Hopf scalar and matrix kernels [PDF]
, 2007 A general theory to factorize the Wiener-Hopf (W-H) kernel using Fredholm Integral Equations (FIE) of the second kind is presented. This technique, hereafter called Fredholm factorization, factorizes the W-H kernel using simple numerical quadrature.
V. Daniele +3 more
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Offshore wind resource assessment based on scarce spatio-temporal measurements using matrix factorization [PDF]
, 2023 In the pre-construction of wind farms, wind resource assessment is of paramount importance. Measurements by lidars are a source of high-fidelity data. However, they are expensive and sparse in space and time.
Ren, Jie +6 more
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CoRR, 2013 We investigate the problem of factorizing a matrix into several sparse matrices and propose an algorithm for this under randomness and sparsity assumptions. This problem can be viewed as a simplification of the deep learning problem where finding a factorization corresponds to finding edges in different layers and values of hidden units.
Behnam Neyshabur, Rina Panigrahy
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Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization [PDF]
, 2013 In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) – a dimensionality reduction technique – to uncover structure in a panel of odor profiles ...
Castro, Jason B. +16 more
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Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization
Cybernetics and Information Technologies, 2014 In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix ...
Bai, Lin, Li Yanbo, Hui Meng
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Musical instrument classification using non-negative matrix factorization algorithms [PDF]
, 2006 14.08.13 KB. Ok to add accepted version to Spiral. IEEEIn this paper, a class of algorithms for automatic classification of individual musical instrument sounds is presented.
Benetos, Emmanouil +5 more
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Uncovering community structures with initialized Bayesian nonnegative matrix factorization. [PDF]
PLoS ONE, 2014 Uncovering community structures is important for understanding networks. Currently, several nonnegative matrix factorization algorithms have been proposed for discovering community structure in complex networks.
Xianchao Tang +3 more
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