Suchergebnisse - formats factorization algorithm

Optimization of the ILU(0) factorization algorithm with the use of compressed sparse row format von Akhunov, R. R., Kuksenko, S. P., Salov, V. K., Gazizov, T. R.

“… Improvements of the ILU(0) factorization algorithm for preconditioning linear algebraic systems with dense matrices are suggested …”
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Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion von Gustavson, Fred G, Wasniewski, Jerzy, Dongarra, Jack J, Langou, Julien

“… We describe a new data format for storing triangular, symmetric, and Hermitian matrices called RFPF …”
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BALS: Blocked Alternating Least Squares for Parallel Sparse Matrix Factorization on GPUs von Chen, Jing, Fang, Jianbin, Liu, Weifeng, Yang, Canqun

“… This article presents an efficient implementation of the alternative least squares (ALS) algorithm called BALS built on top of a new sparse matrix format for parallel matrix factorization …”
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Influence of loop transformations on performance and energy consumption of the multithreded WZ factorization von Bylina, Beata, Bylina, Jaroslaw, Piekarz, Monika

“… As a test, the WZ factorization algorithm is used. The comparison of selected strategies of the loop transformation is done for Intel architecture, namely Cascade Lake …”
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Lempel-Ziv (LZ77) Factorization in Sublinear Time von Kempa, Dominik, Kociumaka, Tomasz

“… This simple routine has numerous applications. Most importantly, the LZ77 factorization is the central component and the computational bottleneck of most existing compression algorithms …”
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Minimal-storage high-performance Cholesky factorization via blocking and recursion von Gustavson, F. G., Jonsson, I.

“… We present a novel practical algorithm for Cholesky factorization when the matrix is stored in packed format by combining blocking and recursion …”
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UNMF: a unified nonnegative matrix factorization for multi-dimensional omics data von Abe, Ko, Shimamura, Teppei

“… Abstract Factor analysis, ranging from principal component analysis to nonnegative matrix factorization, represents a foremost approach in analyzing multi-dimensional data to extract valuable patterns …”
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A Parallel Direct Finite Element Solver Empowered by Machine Learning for Solving Large-Scale Electromagnetic Problems von Wang, Junjie, Zuo, Sheng, Zhao, Xunwang, Tian, Min, Lin, Zhongchao, Zhang, Yu

“… Our proposed solver features adaptive fill-reducing ordering and highly assembled lazy offloading (HALO) factorization …”
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Accelerated sparse nonnegative matrix factorization for unsupervised feature learning von Xie, Ting, Zhang, Hua, Liu, Ruihua, Xiao, Hanguang

“… •We analyzed the convergence of algorithm in theory and proved that the convergence point is KKT point of equivalent model …”
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A factorization scheme for observability analysis in transportation networks von Owais, Mahmoud, Matouk, Ahmed E.

“… Some flow types are difficult to observe directly, such as node pair demand (O/D flow). This study provides a mathematical analysis approach using a factorization scheme to convert conventional traffic assignment mapping into a useful format …”
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Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS von Johnson, Jeanette A. I., Tsang, Ashley P., Mitchell, Jacob T., Zhou, David L., Bowden, Julia, Davis-Marcisak, Emily, Sherman, Thomas, Liefeld, Ted, Loth, Melanie, Goff, Loyal A., Zimmerman, Jacquelyn W., Kinny-Köster, Ben, Jaffee, Elizabeth M., Tamayo, Pablo, Mesirov, Jill P., Reich, Michael, Fertig, Elana J., Stein-O’Brien, Genevieve L.

“… Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology …”
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A distributed packed storage for large dense parallel in-core calculations von Baboulin, Marc, Giraud, Luc, Gratton, Serge, Langou, Julien

“… In this paper we propose a distributed packed storage format that exploits the symmetry or the triangular structure of a dense matrix …”
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A Block Householder–Based Algorithm for the QR Decomposition of Hierarchical Matrices von Griem, Vincent, Le Borne, Sabine

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ISLU: Indexing-Efficient Sparse LU Factorization for Circuit Simulation on GPUs (Invited Paper) von Niu, Dan, Tao, Yiyang, Jin, Zhou, Dong, Yichao, Wang, Chao, Sun, Changyin

“… Sparse LU factorization is a vital technique in solving circuit linear equations, However, irregular data access patterns contribute to unsatisfactory computational efficiency and excessive memory usage …”
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Online product recommendation system using gated recurrent unit with Broyden Fletcher Goldfarb Shanno algorithm von Suresh, A., Carmel Mary Belinda, M. J.

“… However, dealing with the customer feedbacks in text format as an unstructured data is a challenging task, because it is hard to analyze and interpret the information …”
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Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry von Verbeeck, Nico, Caprioli, Richard M., Van de Plas, Raf

“… Research into computational methods for IMS data has touched upon different aspects, including spectral preprocessing, data formats, dimensionality reduction, spatial registration, sample …”
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Algorithms for Sparse Linear Systems von Scott, Jennifer, Tůma, Miroslav

“… This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used …”
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Tensor train factorization under noisy and incomplete data with automatic rank estimation von Xu, Le, Cheng, Lei, Wong, Ngai, Wu, Yik-Chung

“… •Gaussian-product-Gamma prior with sparsity analysis for TT representation.•Variational Inference algorithm with automatic rank selection …”
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Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery von Qian, Yuntao, Xiong, Fengchao, Zeng, Shan, Zhou, Jun, Tang, Yuan Yan

“… Many spectral unmixing approaches ranging from geometry, algebra to statistics have been proposed, in which nonnegative matrix factorization (NMF …”
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(O(N)\) distributed direct factorization of structured dense matrices using runtime systems von Deshmukh, Sameer, Ma, Qinxiang, Yokota, Rio, Bosilca, George

“… )\). The Hierarchically Semi-Separable (HSS) matrix is one such low rank matrix format that can be factorized using a Cholesky-like algorithm called ULV factorization …”
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