Zobrazeno 1 - 10
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pro vyhledávání: '"Gür A."'
Package spar for R builds ensembles of predictive generalized linear models with high-dimensional predictors. It employs an algorithm utilizing variable screening and random projection tools to efficiently handle the computational challenges associat
Externí odkaz:
http://arxiv.org/abs/2411.17808
Autor:
Yahia, Olfa Ben, Ferguson, William, Chakravarty, Sumit, Benchoubane, Nesrine, Kurt, Gunes Karabulut, Gür, Gürkan, Falco, Gregory
The rapid evolution of communication technologies, compounded by recent geopolitical events such as the Viasat cyberattack in February 2022, has highlighted the urgent need for fast and reliable satellite missions for military and civil security oper
Externí odkaz:
http://arxiv.org/abs/2411.12632
Autor:
Vana-Gür, Laura, Hirk, Rainer
In this paper we build a joint model which can accommodate for binary, ordinal and continuous responses, by assuming that the errors of the continuous variables and the errors underlying the ordinal and binary outcomes follow a multivariate normal di
Externí odkaz:
http://arxiv.org/abs/2411.02924
We address the challenge of correlated predictors in high-dimensional GLMs, where regression coefficients range from sparse to dense, by proposing a data-driven random projection method. This is particularly relevant for applications where the number
Externí odkaz:
http://arxiv.org/abs/2410.00971
A first proposal of a sparse and cellwise robust PCA method is presented. Robustness to single outlying cells in the data matrix is achieved by substituting the squared loss function for the approximation error by a robust version. The integration of
Externí odkaz:
http://arxiv.org/abs/2408.15612
In this paper, we show how mixed-integer conic optimization can be used to combine feature subset selection with holistic generalized linear models to fully automate the model selection process. Concretely, we directly optimize for the Akaike and Bay
Externí odkaz:
http://arxiv.org/abs/2404.16560
Autor:
Vana-Gür, Laura
In this paper we propose a multivariate ordinal regression model which allows the joint modeling of three-dimensional panel data containing both repeated and multiple measurements for a collection of subjects. This is achieved by a multivariate autor
Externí odkaz:
http://arxiv.org/abs/2402.00610
Autor:
Guer, Matthieu, Luttmann, Martin, Hergott, Jean-François, Lepetit, Fabien, Ruchon, Olivier Tcherbakoff Thierry, Géneaux, Romain
We report on the generation of optical vortices with few-cycle pulse durations, 500$\mu$J per pulse, at a repetition rate of 1 kHz. To do so, a 25 fs laser beam at 800 nm is shaped with a helical phase and coupled into a hollow core fiber filled with
Externí odkaz:
http://arxiv.org/abs/2312.11087
We examine the linear regression problem in a challenging high-dimensional setting with correlated predictors where the vector of coefficients can vary from sparse to dense. In this setting, we propose a combination of probabilistic variable screenin
Externí odkaz:
http://arxiv.org/abs/2312.00130
Publikováno v:
Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Vol 26, Iss Özel Sayı, Pp 17-34 (2024)
Yapay Sinir Ağları (YSA), makine öğrenmesi alanında yaygın olarak kullanılan etkili bir yöntemdir ve tahmin yapmada başarılı sonuçlar sağlayabilir. YSA, biyolojik sinir sisteminden ilham alınarak matematiksel bir model oluşturur. Bu ç
Externí odkaz:
https://doaj.org/article/37c5b5abbec24d0b93a12f1a5198bdf9
