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of 3 837
pro vyhledávání: '"Insua, A"'
Autor:
López-Reyes, Mauricio, González-Alemán, J. J., Sastre, M., Insua-Costa, D., Bolgiani, P., Martín, M. L.
Hurricane Leslie (2018) was a non-tropical system that lasted for a long time undergoing several transitions between tropical and extratropical states. Its trajectory was highly uncertain and difficult to predict. Here the extratropical transition of
Externí odkaz:
http://arxiv.org/abs/2409.12363
Pricing decisions stand out as one of the most critical tasks a company faces, particularly in today's digital economy. As with other business decision-making problems, pricing unfolds in a highly competitive and uncertain environment. Traditional an
Externí odkaz:
http://arxiv.org/abs/2409.00444
Autor:
Corrales, Daniel, Santos-Lozano, Alejandro, López-Ortiz, Susana, Lucia, Alejandro, Insua, David Ríos
Background and Objective: Only about 14 % of eligible EU citizens finally participate in colorectal cancer (CRC) screening programs despite it being the third most common type of cancer worldwide. The development of CRC risk models can enable predict
Externí odkaz:
http://arxiv.org/abs/2408.08618
This paper addresses decision-aiding problems that involve multiple objectives and uncertain states of the world. Inspired by the capability approach, we focus on cases where a policy maker chooses an act that, combined with a state of the world, lea
Externí odkaz:
http://arxiv.org/abs/2405.13647
Autor:
Bobes-Bascarán, José, Mosqueira-Rey, Eduardo, Fernández-Leal, Ángel, Hernández-Pereira, Elena, Alonso-Ríos, David, Moret-Bonillo, Vicente, Figueirido-Arnoso, Israel, Vidal-Ínsua, Yolanda
This paper presents a comprehensive study on the evaluation of explanatory capabilities of machine learning models, with a focus on Decision Trees, Random Forest and XGBoost models using a pancreatic cancer dataset. We use Human-in-the-Loop related t
Externí odkaz:
http://arxiv.org/abs/2403.19820
We introduce a novel estimator for predicting outcomes in the presence of hidden confounding across different distributional settings without relying on regularization or a known causal structure. Our approach is based on parametrizing the dependence
Externí odkaz:
http://arxiv.org/abs/2402.15502
In domains such as homeland security, cybersecurity and competitive marketing, it is frequently the case that analysts need to forecast adversarial actions that impact the problem of interest. Standard structured expert judgement elicitation techniqu
Externí odkaz:
http://arxiv.org/abs/2402.03538
The introduction of the European Union Artificial Intelligence Act, the NIST Artificial Intelligence Risk Management Framework, and related norms demands a better understanding and implementation of novel risk analysis approaches to evaluate systems
Externí odkaz:
http://arxiv.org/abs/2401.01630
Autor:
Dempsey, Paula R., Insua, Glenda M., Armstrong, Annie R., Hudson, Holly Joy, Caragher, Kristyn, McGregor, Mariah
Publikováno v:
Reference Services Review, 2024, Vol. 52, Issue 3, pp. 420-449.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/RSR-05-2024-0024
Publikováno v:
Communications Chemistry, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract As in natural cytoskeletons, the cooperative assembly of fibrillar networks can be hosted inside compartments to engineer biomimetic functions, such as mechanical actuation, transport, and reaction templating. Coacervates impose an optimal l
Externí odkaz:
https://doaj.org/article/d69dbbbf6ed8471187a4b1456d32679a