Zobrazeno 1 - 10
of 7 569
pro vyhledávání: '"A. Martínez-Fernández"'
Autor:
E. Nagore, D. Moreno-Ramírez, P. Ortiz-Romero, E. Martín-Sánchez, A. Martínez-Fernández, S. Puig
Publikováno v:
Actas Dermo-Sifiliográficas, Vol 113, Iss 4, Pp 354-362 (2022)
Resumen: Antecedentes y objetivo: Para estimar la carga real del melanoma y el impacto de las nuevas terapias adyuvantes sobre las recaídas y la supervivencia, se precisa conocer con mayor exactitud la incidencia por estadios y analizar la transici
Externí odkaz:
https://doaj.org/article/f5276559962a4a248a042bc9bcb46164
Autor:
de Martino, Vincenzo, Castaño, Joel, Palomba, Fabio, Franch, Xavier, Martínez-Fernández, Silverio
Context: The emergence of Large Language Models (LLMs) has significantly transformed Software Engineering (SE) by providing innovative methods for analyzing software repositories. Objectives: Our objective is to establish a practical framework for fu
Externí odkaz:
http://arxiv.org/abs/2411.09974
Background: Open-Source Pre-Trained Models (PTMs) and datasets provide extensive resources for various Machine Learning (ML) tasks, yet these resources lack a classification tailored to Software Engineering (SE) needs. Aims: We apply an SE-oriented c
Externí odkaz:
http://arxiv.org/abs/2411.09683
The proliferation of Machine Learning (ML) models and their open-source implementations has transformed Artificial Intelligence research and applications. Platforms like Hugging Face (HF) enable the development, sharing, and deployment of these model
Externí odkaz:
http://arxiv.org/abs/2411.09645
As machine learning (ML) and artificial intelligence (AI) technologies become increasingly prevalent in society, concerns about their environmental sustainability have grown. Developing and deploying ML-enabled systems, especially during training and
Externí odkaz:
http://arxiv.org/abs/2410.06708
Background: Given the fast-paced nature of today's technology, which has surpassed human performance in tasks like image classification, visual reasoning, and English understanding, assessing the impact of Machine Learning (ML) on energy consumption
Externí odkaz:
http://arxiv.org/abs/2409.12878
A synthetic Mirnov coils diagnostic is presented and used to study the capabilities of the poloidal array of single-axis coils and the two helical arrays of tri-axial coils installed in the TJ-II stellarator. This tool integrates the plasma currents
Externí odkaz:
http://arxiv.org/abs/2409.04221
Autor:
E. Nagore, D. Moreno-Ramírez, P. Ortiz-Romero, E. Martín-Sánchez, A. Martínez-Fernández, S. Puig
Publikováno v:
Actas Dermo-Sifiliográficas, Vol 113, Iss 4, Pp T354-T362 (2022)
Background and objective: Accurate information on the incidence of melanoma by stage and a better understanding of transition between stages are important for determining the burden of disease and assessing the impact of new adjuvant therapies on rec
Externí odkaz:
https://doaj.org/article/4cee1536385f4e08b5446101e2c4f0d0
Autor:
Omar, Rafiullah, Bogner, Justus, Muccini, Henry, Lago, Patricia, Martínez-Fernández, Silverio, Franch, Xavier
Background: Machine learning (ML) model composition is a popular technique to mitigate shortcomings of a single ML model and to design more effective ML-enabled systems. While ensemble learning, i.e., forwarding the same request to several models and
Externí odkaz:
http://arxiv.org/abs/2407.02914
The latest advancements in machine learning, specifically in foundation models, are revolutionizing the frontiers of existing software engineering (SE) processes. This is a bi-directional phenomona, where 1) software systems are now challenged to pro
Externí odkaz:
http://arxiv.org/abs/2406.18142