Results 11 to 20 of about 6,086,701 (288)
Determining the dimension of the central subspace and central mean subspace
Biometrika, 2008 The central subspace and central mean subspace are two important targets of sufficient dimension reduction. We propose a weighted chi-squared test to determine their dimensions based on matrices whose column spaces are exactly equal to the central ...
Peng Zeng
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MOMENT KERNELS FOR T-CENTRAL SUBSPACE [PDF]
, 2020 The T-central subspace allows one to perform sufficient dimension reduction for any statistical functional of interest. We propose a general estimator using a third moment kernel to estimate the T-central subspace.
Ren, Weihang
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MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi-Scale Information and Metric Learning Framework for scDNAm Data. [PDF]
Adv Sci (Weinh)MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Jia Y, Li S, Tang S, Gu K, Chen S.
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Transformed central quantile subspace [PDF]
Statistics, 2021 arXiv admin note: text overlap with arXiv:1906 ...
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Subspace discovery for video anomaly detection [PDF]
, 2010 PhDIn automated video surveillance anomaly detection is a challenging task. We address this task as a novelty detection problem where pattern description is limited and labelling information is available only for a small sample of normal instances.
Tziakos, Ioannis
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Central subspaces review: methods and applications
Statistics Surveys, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rodrigues, SA, Huggins, R, Liquet, B
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Central quantile subspace [PDF]
Statistics and Computing, 2019 Quantile regression (QR) is becoming increasingly popular due to its relevance in many scientific investigations. There is a great amount of work about linear and nonlinear QR models. Specifically, nonparametric estimation of the conditional quantiles received particular attention, due to its model flexibility.
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CS Decomposition Based Bayesian Subspace Estimation [PDF]
, 2012 In numerous applications, it is required to estimate the principal subspace of the data, possibly from a very limited number of samples. Additionally, it often occurs that some rough knowledge about this subspace is available and could be used to improve
Besson, Olivier +2 more
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Central Subspaces of Banach Spaces
Journal of Approximation Theory, 2000 Let \(X\) be a Banach space. A subspace \(Y \subset X\) is called a central subspace (\(C\)-subspace) of \(X\) if every finite family of closed balls with centers in \(Y\) that intersects in \(X\) also intersects in \(Y\). In particular \(X\) is said to be generalized center (GC) if and only if \(X\) is a \(C\)-subspace of \(X^{**}\).
Bandyopadhyay, Pradipta, Rao, T.S.S.R.K.
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Intersection Properties of Balls in Banach Spaces
Journal of Function Spaces and Applications, 2013 We introduce a weaker notion of central subspace called almost central subspace, and we study Banach spaces that belong to the class (GC), introduced by Veselý (1997). In particular, we prove that if is an almost central subspace of a Banach space such
C. R. Jayanarayanan
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