Výsledky vyhledávání - "data matrix"

Robust low-rank data matrix approximations Autor Feng, XingDong, He, XuMing

“… We consider the problem of estimating a low-rank mean matrix when the data matrix is subject to measurement errors as well as gross outliers in some of…”
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Designing research with in-built differentiated replication Autor Uncles, Mark D., Kwok, Simon

“…Replication is central to normal scientific investigation. This fact is widely accepted in business disciplines. However, many researchers are uncertain how to…”
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Iterative angle-and-time-domain gating technique for time-reversal MUSIC imaging Autor Choi, Heedong, Ogawa, Yasutaka, Nishimura, Toshihiko, Ohgane, Takeo

“… Although the one-dimensional gating technique for TR-MUSIC mitigates the effect of noise as well as reduces the required number of antenna elements, the resulting image is subject to focusing errors…”
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New Trends in Production and Operations Management

“… This includes all subjects in the operations, design, and supply chain management of products and processes, i.e…”
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Low-Rank Expectile Representations of a Data Matrix, with Application to Diurnal Heart Rates Autor Ouyang, Shuge, Tang, Yunxuan, Benjamin Osafo Agyare

“… Here we present a framework for low-rank expectile analysis of a data matrix that incorporates both additive and multiplicative effects, utilizing expectile loss, and accommodating arbitrary patterns of missing data…”
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A novel subject-wise dictionary learning approach using multi-subject fMRI spatial and temporal components Autor Khalid, Muhammad Usman, Nauman, Malik Muhammad

“… Considering that subject-wise (sw) data matrix can be decomposed into the sparse linear combination of multi-subject (MS…”
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A simultaneous CONCOR algorithm for the analysis of two partitioned matrices Autor Lafosse, Roger, ten Berge, Jos M.F.

“…A standard approach to derive underlying components from two or more data matrices, holding data from the same individuals or objects, is the (generalized…”
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Simultaneous analysis of coupled data matrices subject to different amounts of noise Autor Wilderjans, Tom F., Ceulemans, Eva, Van Mechelen, Iven, van den Berg, Robert A.

“… being the same in all matrices. To obtain an overall picture of the mechanisms that play a role in the different data matrices, the information in these matrices needs to be integrated…”
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Enhanced Technique for Accurate Localization and Life-Sign Detection of Human Subjects Using Beam-Steering Radar Architectures Autor Mercuri, Marco, Sacco, Giulia, Hornung, Rainer, Visser, Huib, Lorato, Ilde, Pisa, Stefano, Veltri, Pierangelo, Dolmans, Guido

“… (respiration and heart rates) and 2-D positions (range and azimuth information). The spectral analysis, the data matrix generation and the signal processing…”
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Quantitative sensory testing response patterns to capsaicin- and ultraviolet-B-induced local skin hypersensitization in healthy subjects: a machine-learned analysis Autor Lötsch, Jörn, Geisslinger, Gerd, Heinemann, Sarah, Lerch, Florian, Oertel, Bruno G, Ultsch, Alfred

“… (German Research Network on Neuropathic Pain). This study provided a 246 × 10-sized data matrix…”
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2 - Methodology Autor Ravindra K. Dhir, Jorge de Brito, Gurmel S. Ghataora, Chao Qun Lye

“… The second stage involves sorting of the literature, mining the data from the sourced publications and parking this information to build the data matrix…”
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Robust least squares for quantized data matrices Autor Becker, Stephen, Clancy, Richard J

“…In this paper we formulate and solve a robust least squares problem for a system of linear equations subject to quantization error in the data matrix…”
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Mimicking Complexity of Structured Data Matrix’s Information Content: Categorical Exploratory Data Analysis Autor Hsieh, Fushing, Chou, Elizabeth P., Chen, Ting-Li

“…We develop Categorical Exploratory Data Analysis (CEDA) with mimicking to explore and exhibit the complexity of information content that is contained within any data matrix…”
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A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses Autor Chen, Ling, Gu, Yuqi

“… Our approach hinges on the observation that the expectation of the data matrix has a low-rank decomposition under a GoM model…”
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The SIMCLAS Model: Simultaneous Analysis of Coupled Binary Data Matrices with Noise Heterogeneity Between and Within Data Blocks Autor Wilderjans, Tom F., Ceulemans, E., Van Mechelen, I.

“…In many research domains different pieces of information are collected regarding the same set of objects. Each piece of information constitutes a data block,…”
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Incomplete Repeated Measures Data Analysis in the Presence of Treatment Effects Autor Carriere, Keumhee Chough

“…This article illustrates an analysis strategy for repeated measures data where some of the measurements are missing from the subjects on one or more occasions, with a special application to data…”
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Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis Autor Ramkumar, Pavan, Parkkonen, Lauri, Hari, Riitta, Hyvärinen, Aapo

“…) data is usually performed over the temporal dimension: each channel is one row of the data matrix, and a linear transformation maximizing the independence of component time courses is sought…”
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Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations Autor Zhang, Shu, Li, Xiang, Lv, Jinglei, Jiang, Xi, Guo, Lei, Liu, Tianming

“… Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix…”
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The Growth of Contemporary Music Subject and the Reform of Music Teaching in Universities Autor Zhao, Binbin, Razzouk, Rim

“…) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to…”
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PROJECTED PRINCIPAL COMPONENT ANALYSIS IN FACTOR MODELS Autor Fan, Jianqing, Liao, Yuan, Wang, Weichen

“…) data matrix onto a given linear space spanned by covariates. When it applies to high-dimensional factor analysis, the projection removes noise components…”
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