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pro vyhledávání: '"Glad Ingrid K"'
Longevity and safety of lithium-ion batteries are facilitated by efficient monitoring and adjustment of the battery operating conditions. Hence, it is crucial to implement fast and accurate algorithms for State of Health (SoH) monitoring on the Batte
Externí odkaz:
http://arxiv.org/abs/2102.08111
Autor:
Brandsæter, Andreas, Glad, Ingrid K.
Publikováno v:
Data Min Knowl Disc (2022)
This paper proposes a novel approach to explain the predictions made by data-driven methods. Since such predictions rely heavily on the data used for training, explanations that convey information about how the training data affects the predictions a
Externí odkaz:
http://arxiv.org/abs/2012.03625
Autor:
Drabløs Finn, Clancy Trevor, Liestøl Knut, Holden Marit, Holden Lars, Glad Ingrid K, Rydbeck Halfdan, Gundersen Sveinung, Sandve Geir K, Ferkingstad Egil, Johansen Morten, Nygaard Vegard, Tøstesen Eivind, Frigessi Arnoldo, Hovig Eivind
Publikováno v:
BMC Genomics, Vol 12, Iss 1, p 353 (2011)
Abstract Background Transcription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studie
Externí odkaz:
https://doaj.org/article/950c378ca4824fd9ae1ec301dfb8a91f
Autor:
Cepko Connie L, Ohno-Machado Lucila, Trimarchi Jeff, Kuo Winston P, Holden Marit, Liu Fang, Nygaard Vigdis, Frigessi Arnoldo, Glad Ingrid K, Wiel Mark, Hovig Eivind, Lyng Heidi
Publikováno v:
BMC Genomics, Vol 9, Iss 1, p 258 (2008)
Abstract Background Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, suc
Externí odkaz:
https://doaj.org/article/e07e0ff0cc1144b8ab69444aa3df9ddf
Autor:
Tveten, Martin, Glad, Ingrid K.
When applying principal component analysis (PCA) for dimension reduction, the most varying projections are usually used in order to retain most of the information. For the purpose of anomaly and change detection, however, the least varying projection
Externí odkaz:
http://arxiv.org/abs/1908.02029
Akademický článek
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Autor:
Brandsæter, Andreas, Glad, Ingrid K.
Publikováno v:
Data Mining & Knowledge Discovery; Sep2024, Vol. 38 Issue 5, p2633-2664, 32p
We consider the problems of variable selection and estimation in nonparametric additive regression models for high-dimensional data. In recent years, several methods have been proposed to model nonlinear relationships when the number of covariates ex
Externí odkaz:
http://arxiv.org/abs/1310.1282
Publikováno v:
In Expert Systems With Applications 1 May 2019 121:418-437
Autor:
Bergersen, Linn Cecilie, Ahmed, Ismaïl, Frigessi, Arnoldo, Glad, Ingrid K., Richardson, Sylvia
We propose a new approach to safe variable preselection in high-dimensional penalized regression, such as the lasso. Preselection - to start with a manageable set of covariates - has often been implemented without clear appreciation of its potential
Externí odkaz:
http://arxiv.org/abs/1210.0380