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A More Efficient and Practical Modified Nyström Method

open access: yesMathematics, 2023
In this paper, we propose an efficient Nyström method with theoretical and empirical guarantees. In parallel computing environments and for sparse input kernel matrices, our algorithm can have computation efficiency comparable to the conventional Nyström
Wei Zhang   +3 more
doaj   +1 more source

Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation

open access: yesMathematics, 2022
For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b.
Rebeca Peláez   +2 more
doaj   +1 more source

Weighted Nash Inequalities [PDF]

open access: yes, 2010
Nash or Sobolev inequalities are known to be equivalent to ultracontractive properties of Markov semigroups, hence to uniform bounds on their kernel densities.
Bakry, Dominique   +3 more
core   +6 more sources

Free-Breathing and Ungated Cardiac MRI Reconstruction Using a Deep Kernel Representation

open access: yesApplied Sciences, 2023
Free-breathing and ungated cardiac MRI is a challenging problem due to the cardiac motion and respiration motion, which are not tracked. In this work, we propose an unsupervised deep kernel method for reconstructing real-time free-breathing and ungated ...
Qing Zou   +3 more
doaj   +1 more source

Further enumeration results concerning a recent equivalence of restricted inversion sequences [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2022
Let asc and desc denote respectively the statistics recording the number of ascents or descents in a sequence having non-negative integer entries.
Toufik Mansour, Mark Shattuck
doaj   +1 more source

Diagrams for heat kernel expansions [PDF]

open access: yes, 2001
A diagramatic heat kernel expansion technique is presented. The method is especially well suited to the small-derivative expansion of the heat kernel, but it can also be used to reproduce the results obtained by the approach known as covariant ...
de Bruno F   +14 more
core   +2 more sources

Debiased Maximum Likelihood Estimators of Hazard Ratios Under Kernel-Based Machine Learning Adjustment

open access: yesMathematics
Previous studies have shown that hazard ratios between treatment groups estimated with the Cox model are uninterpretable because the unspecified baseline hazard of the model fails to identify temporal change in the risk-set composition due to treatment ...
Takashi Hayakawa, Satoshi Asai
doaj   +1 more source

Kernel Current Source Density Method [PDF]

open access: yesNeural Computation, 2011
Local field potentials (LFP), the low-frequency part of extracellular electrical recordings, are a measure of the neural activity reflecting dendritic processing of synaptic inputs to neuronal populations. To localize synaptic dynamics, it is convenient, whenever possible, to estimate the density of transmembrane current sources (CSD) generating the ...
Wójcik Daniel K   +3 more
openaire   +3 more sources

Functional Ergodic Time Series Analysis Using Expectile Regression

open access: yesMathematics, 2022
In this article, we study the problem of the recursive estimator of the expectile regression of a scalar variable Y given a random variable X that belongs in functional space.
Fatimah Alshahrani   +5 more
doaj   +1 more source

Bayesian Kernel Methods

open access: yesInternational Journal of Big Data and Analytics in Healthcare, 2021
In the healthcare industry, sources look after different customers with diverse diseases and complications. Thus, at the source, a great amount of data in all aspects like status of the patients, behaviour of the diseases, etc. are collected, and now it becomes the job of the practitioner at source to use the available data for diagnosing the diseases ...
Arti Saxena, Vijay Kumar
openaire   +2 more sources

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