Results 1 to 10 of about 26,367 (267)
Recommendation Algorithm Using SVD and Weight Point Rank (SVD-WPR)
Big Data and Cognitive Computing, 2022 One of the most prevalent recommendation systems is ranking-oriented collaborative filtering which employs ranking aggregation. The collaborative filtering study recently applied the ranking aggregation that considers the weight point of items to achieve a more accurate recommended ranking.
Triyanna Widiyaningtyas +1 more
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Dimensionality Reduction: Challenges and Solutions [PDF]
ITM Web of Conferences, 2022 The use of dimensionality reduction techniques is a keystone for analyzing and interpreting high dimensional data. These techniques gather several data features of interest, such as dynamical structure, input-output relationships, the correlation between
Ahmad Noor, Nassif Ali Bou
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Robust Differentiable SVD [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) method to approximate them.
Wei Wang 0108 +4 more
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On GROUSE and incremental SVD [PDF]
2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 GROUSE (Grassmannian Rank-One Update Subspace Estimation) is an incremental algorithm for identifying a subspace of Rn from a sequence of vectors in this subspace, where only a subset of components of each vector is revealed at each iteration. Recent analysis has shown that GROUSE converges locally at an expected linear rate, under certain assumptions.
Laura Balzano, Stephen J. Wright 0001
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Journal Focus Action of Research Mathematic, 2022 Model Generalized AMMI (GAMMI) merupakan perluasan dari model AMMI (Additive Main Effect and Multiplicative Interaction). Model GAMMI melibatkan konsep Generalized Linear Model (GLM) pada variabel responnya.
Kurnia Ahadiyah, Ardiana Fatma Dewi
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CoRR, 2021 The code can be accessed through https://github.com/Vicky-Zh/E ...
Huiwen Wang, Yanwen Zhang, Jichang Zhao
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Introducing a New Hybrid Adaptive Local Optimal Low Rank Approximation Method for Denoising Images [PDF]
International Journal of Industrial Electronics, Control and Optimization, 2020 This paper aimed to formulate image noise reduction as an optimization problem and denoise the target image using matrix low rank approximation. Considering the fact that the smaller pieces of an image are more similar (more dependent) in natural images;
sadegh kalantari +2 more
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Journal of High Energy Physics, 2023 Abstract In this paper, we introduce a new quantity called SVD entanglement entropy. This is a generalization of entanglement entropy in that it depends on two different states, as in pre- and post-selection processes. This SVD entanglement entropy takes non-negative real values and is bounded by the logarithm of the Hilbert space ...
Arthur J. Parzygnat +3 more
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On the Computation of the SVD of Fourier Submatrices
Journal of Scientific Computing, 2023 Contiguous submatrices of the Fourier matrix are known to be ill-conditioned. In a recent paper in SIAM Review A. Barnett has provided new bounds on the rate of ill-conditioning of the discrete Fourier submatrices. In this paper we focus on the corresponding singular value decomposition.
Huybrechs, Daan +2 more
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A COURTYARD HOUSE – SIHEYUAN 四合院 AS THE DWELLING PLACE OF THE TRADITIONAL CHINESE FAMILY
Forum Teologiczne, 2020 A Chinese courtyard house, called in Chinese siheyuan, equipped with a single entrance and with one or more open courtyards encompassed by one-storey buildings, represents traditional house dwelling in China.
Zbigniew Wesołowski SVD
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