Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Xinghao Qiao"'
Publikováno v:
Symmetry, Vol 11, Iss 3, p 427 (2019)
Identifying critical components are of great significance to the overall reliability of service-oriented systems (SOSs). As the size of the SOS increases, identifying critical components in the process of predicting the SOS reliability can reduce the
Externí odkaz:
https://doaj.org/article/4f554ecd1e02418598ea52a24a99804f
Publikováno v:
Symmetry, Vol 11, Iss 3, p 392 (2019)
Using semantic information can help to accurately find suitable services from a variety of available (different semantics) services, and the semantic information of Web services can be described in detail in a Web service knowledge graph. In this pap
Externí odkaz:
https://doaj.org/article/91ea0667d6ce4ef5839c2a227dd06111
Publikováno v:
Journal of Business & Economic Statistics. 40:444-457
Functional linear regression is an important topic in functional data analysis. It is commonly assumed that samples of the functional predictor are independent realizations of an underlying stochastic process, and are observed over a grid of points c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3923c96aa0bc50a0b879991808d2f599
https://doi.org/10.1080/07350015.2020.1832503
https://doi.org/10.1080/07350015.2020.1832503
Summary We consider estimating a functional graphical model from multivariate functional observations. In functional data analysis, the classical assumption is that each function has been measured over a densely sampled grid. However, in practice the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af6da3e3e4ab2c83ce167674759420b8
http://eprints.lse.ac.uk/103120/
http://eprints.lse.ac.uk/103120/
Publikováno v:
Journal of the American Statistical Association. 114:211-222
Graphical models have attracted increasing attention in recent years, especially in settings involving high-dimensional data. In particular, Gaussian graphical models are used to model the conditional dependence structure among multiple Gaussian rand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45eb31726c5b1966af27a0f7a0934a1f
https://doi.org/10.1080/01621459.2017.1390466
https://doi.org/10.1080/01621459.2017.1390466
Many scientific and economic applications involve the statistical learning of high-dimensional functional time series, where the number of functional variables is comparable to, or even greater than, the number of serially dependent functional observ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e9f0ab9609eb86bbcfe9775321999b5
Publikováno v:
Symmetry, Vol 11, Iss 3, p 392 (2019)
Symmetry; Volume 11; Issue 3; Pages: 392
Symmetry; Volume 11; Issue 3; Pages: 392
Using semantic information can help to accurately find suitable services from a variety of available (different semantics) services, and the semantic information of Web services can be described in detail in a Web service knowledge graph. In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab0bbcebaa6ba305f593f526cc0b4c7a
http://www.mdpi.com/2073-8994/11/3/392
http://www.mdpi.com/2073-8994/11/3/392
Publikováno v:
Journal of Business & Economic Statistics; Jan2022, Vol. 40 Issue 1, p444-457, 14p
Panel data analysis is an important topic in statistics and econometrics. Traditionally, in panel data analysis, all individuals are assumed to share the same unknown parameters, e.g. the same coefficients of covariates when the linear models are use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72803f252a5514caebbfa3e19a4a3abd
http://arxiv.org/abs/1706.00857
http://arxiv.org/abs/1706.00857
Publikováno v:
Journal of Physics: Conference Series. 1213:042015
This paper proposed a recommendation algorithm based on knowledge graph representation learning (RABKGRL).The algorithm embeds the entities and relationships of the knowledge graph into the low-dimensional vector space. The relationship information o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f37caabd9f65a0f564aace7f4cf9d18d
https://doi.org/10.1088/1742-6596/1213/4/042015
https://doi.org/10.1088/1742-6596/1213/4/042015