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Published in 2018 at "Calcolo"
DOI: 10.1007/s10092-018-0266-3
Abstract: Generalized cross-validation (GCV) is a popular tool for specifying the tuning parameter in linear regression model or equivalently the regularization parameter in Tikhonov regularization. In this work, we are concerned with the estimation and minimization…
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Keywords:
function;
generalized cross;
cross validation;
statistical approach ... See more keywords
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Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.09.130
Abstract: Abstract In this paper, we study the asymptotic properties of the generalized cross validation (GCV) hyperparameter estimator and establish its connection with the Stein’s unbiased risk estimators (SURE) as well as the mean squared error…
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Keywords:
properties generalized;
generalized cross;
cross validation;
asymptotic properties ... See more keywords
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Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2025.3552603
Abstract: Integrating prior knowledge of neurophysiology into neural network architecture enhances the performance of emotion decoding. While numerous techniques emphasize learning spatial and short-term temporal patterns, there has been a limited emphasis on capturing the vital…
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Keywords:
eeg emotion;
emotion;
generalized cross;
novel transformer ... See more keywords
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Published in 2020 at "Advances in Mechanical Engineering"
DOI: 10.1177/1687814020966539
Abstract: Generalized cross-spring pivots (CSPs) are widely used as revolute joints in precision machinery. However, pseudo-rigid-body (PRB) models cannot capture the parasitic motions of a generalized CSP exactly under combined loads; moreover, the characteristic parameters used…
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Keywords:
combined loads;
generalized cross;
model;
spring ... See more keywords