Zobrazeno 1 - 10
of 1 711
pro vyhledávání: '"Gayán, P."'
This study explores the use of Recurrent Neural Networks (RNN) for real-time cryptocurrency price prediction and optimized trading strategies. Given the high volatility of the cryptocurrency market, traditional forecasting models often fall short. By
Externí odkaz:
http://arxiv.org/abs/2411.05829
In the data-driven world of actuarial science, machine learning (ML) plays a crucial role in predictive modeling, enhancing risk assessment and pricing strategies. Neural networks, specifically combined actuarial neural networks (CANN), are vital for
Externí odkaz:
http://arxiv.org/abs/2410.12824
Autor:
Ravikumar, Shruthi, Hamilton, Margaret, Thevathayan, Charles, Spichkova, Maria, Ali, Kashif, Wijesinghe, Gayan
Many students in introductory programming courses fare poorly in the code writing tasks of the final summative assessment. Such tasks are designed to assess whether novices have developed the analytical skills to translate from the given problem doma
Externí odkaz:
http://arxiv.org/abs/2404.02464
Autor:
Gerardo Garzón González, Tamara Alonso Safont, Oscar Aguado Arroyo, Cristina Villanueva Sanz, Arancha Luaces Gayán, Esther Zamarrón Fraile, Juan José Jurado Balbuena, Inmaculada Mediavilla Herrera, Research Team “TriggerPrim®”
Publikováno v:
BMC Primary Care, Vol 25, Iss 1, Pp 1-10 (2024)
Abstract Background The COVID-19 pandemic generated or accelerated healthcare changes, some of which persist thereafter (e.g., healthcare reorganisation, remote consultation). Such changes entail novel risks for patient safety. Methods Aim To compare
Externí odkaz:
https://doaj.org/article/e510f0aa813a403da9d15b2fb8b3de50
Autor:
Naranpanawa, Nathasha, Soyer, H. Peter, Mothershaw, Adam, Kulatilleke, Gayan K., Ge, Zongyuan, Betz-Stablein, Brigid, Chandra, Shekhar S.
An ugly duckling is an obviously different skin lesion from surrounding lesions of an individual, and the ugly duckling sign is a criterion used to aid in the diagnosis of cutaneous melanoma by differentiating between highly suspicious and benign les
Externí odkaz:
http://arxiv.org/abs/2309.09689
Autor:
Manocchio, Liam Daly, Layeghy, Siamak, Lo, Wai Weng, Kulatilleke, Gayan K., Sarhan, Mohanad, Portmann, Marius
This paper presents the FlowTransformer framework, a novel approach for implementing transformer-based Network Intrusion Detection Systems (NIDSs). FlowTransformer leverages the strengths of transformer models in identifying the long-term behaviour a
Externí odkaz:
http://arxiv.org/abs/2304.14746
Metric learning aims to learn distances from the data, which enhances the performance of similarity-based algorithms. An author style detection task is a metric learning problem, where learning style features with small intra-class variations and lar
Externí odkaz:
http://arxiv.org/abs/2212.08184
Machine Learning (ML) approaches have been used to enhance the detection capabilities of Network Intrusion Detection Systems (NIDSs). Recent work has achieved near-perfect performance by following binary- and multi-class network anomaly detection tas
Externí odkaz:
http://arxiv.org/abs/2212.07558
Contrastive learning has recently achieved remarkable success in many domains including graphs. However contrastive loss, especially for graphs, requires a large number of negative samples which is unscalable and computationally prohibitive with a qu
Externí odkaz:
http://arxiv.org/abs/2209.14067
With growing credit card transaction volumes, the fraud percentages are also rising, including overhead costs for institutions to combat and compensate victims. The use of machine learning into the financial sector permits more effective protection a
Externí odkaz:
http://arxiv.org/abs/2208.11904