Zobrazeno 1 - 10
of 7 272
pro vyhledávání: '"José A, Hernández"'
Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used for ML prototyping and data analysis. However, due to their de
Externí odkaz:
http://arxiv.org/abs/2411.16795
Motivation: Automated bug detection in dynamically typed languages such as Python is essential for maintaining code quality. The lack of mandatory type annotations in such languages can lead to errors that are challenging to identify early with tradi
Externí odkaz:
http://arxiv.org/abs/2411.15368
Autor:
Benjamin, Ojeda-Magaña, Ruben, Ruelas, Joel, Quintanilla-Dominguez, Leopoldo, Gomez-Barba, Juan, Lopez de Herrera, Jose, Robledo-Hernandez, Ana, Tarquis
Publikováno v:
Computers and Electronics in Agriculture, Volume 172, 2020, 105289, ISSN 0168-1699
The acorn is the fruit of the oak and is an important crop in the Spanish dehesa extreme\~na, especially for the value it provides in the Iberian pig food to obtain the "acorn" certification. For this reason, we want to maximise the production of Ibe
Externí odkaz:
http://arxiv.org/abs/2408.03542
Language models of code have demonstrated state-of-the-art performance across various software engineering and source code analysis tasks. However, their demanding computational resource requirements and consequential environmental footprint remain a
Externí odkaz:
http://arxiv.org/abs/2407.04147
Autor:
Campos, Enrique Mármol, Vidal, Aurora González, Ramos, José Luis Hernández, Skarmeta, Antonio
Federated Learning (FL) has become an attractive approach to collaboratively train Machine Learning (ML) models while data sources' privacy is still preserved. However, most of existing FL approaches are based on supervised techniques, which could re
Externí odkaz:
http://arxiv.org/abs/2405.09903
Autor:
Campos, Enrique Mármol, Vidal, Aurora González, Ramos, José Luis Hernández, Skarmeta, Antonio
Federated Learning (FL) represents a promising approach to typical privacy concerns associated with centralized Machine Learning (ML) deployments. Despite its well-known advantages, FL is vulnerable to security attacks such as Byzantine behaviors and
Externí odkaz:
http://arxiv.org/abs/2402.10082
Motivation. Large language models (LLMs) have exhibited remarkable proficiency in diverse software engineering (SE) tasks. Handling such tasks typically involves acquiring foundational coding knowledge on large, general-purpose datasets during a pre-
Externí odkaz:
http://arxiv.org/abs/2401.07930
Autor:
Brandt, Bastian B., Endrődi, Gergely, Hernández, José Javier Hernández, Markó, Gergely, Pannullo, Laurin
In this proceedings article we present a selected set of our lattice results regarding the effect that background electromagnetic fields have on the topology of QCD. In particular, we report on the lattice spacing-dependence of the axion-photon coupl
Externí odkaz:
http://arxiv.org/abs/2312.14660
An important yet underexplored question in the PAC-Bayes literature is how much tightness we lose by restricting the posterior family to factorized Gaussian distributions when optimizing a PAC-Bayes bound. We investigate this issue by estimating data
Externí odkaz:
http://arxiv.org/abs/2310.20053
Autor:
Sara I. Olvera-Cruz, Araceli Cano-Estrada, José Á. Hernández-Mariano, Ana C. Castañeda-Márquez, Yaneth C. O. Orihuela, María A. Mejía-Blanquel
Publikováno v:
Journal of Family Medicine and Primary Care, Vol 13, Iss 10, Pp 4521-4527 (2024)
Purpose Previous evidence suggests that non-adherence to medication among patients with chronic diseases might negatively affect their health-related quality of life (HRQoL); however, the evidence in adults with type 2 diabetes (T2D) is not conclusiv
Externí odkaz:
https://doaj.org/article/6e883514ea9f43a4bd732772c5e79c00
