Zobrazeno 1 - 10
of 34 216
pro vyhledávání: '"LEITÃO, A."'
Autor:
Adisa, Olumide, Blay, Enio Alterman, Asgari, Yasaman, Di Bona, Gabriele, Dies, Samantha, Jaramillo, Ana Maria, Resende, Paulo H., Leitao, Ana Maria de Sousa
Complexity science, despite its broad scope and potential impact, has not kept pace with fields like artificial intelligence, biotechnology and social sciences in addressing ethical concerns. The field lacks a comprehensive ethical framework, leaving
Externí odkaz:
http://arxiv.org/abs/2409.02002
Exchange bias is applied ubiquitously throughout the spintronics industry for pinning magnetic moment in an orientation robust against external magnetic field disturbances. Enabling efficient manipulation of the exchange-biased pinning direction is k
Externí odkaz:
http://arxiv.org/abs/2408.15672
Autor:
Fernández, J. L., Ferreiro, A. M., García, J. A., Leitao, A., López-Salas, J. G., Vázquez, C.
Publikováno v:
J.L. Fern\'andez, et.al. , Static and dynamic SABR stochastic volatility models: Calibration and option pricing using GPUs, Mathematics and Computers in Simulation, Volume 94, 2013, Pages 55-75
For the calibration of the parameters in static and dynamic SABR stochastic volatility models, we propose the application of the GPU technology to the Simulated Annealing global optimization algorithm and to the Monte Carlo simulation. This calibrati
Externí odkaz:
http://arxiv.org/abs/2407.20713
Autor:
Villarino, Joel P., Leitao, Álvaro
The present work addresses the challenge of training neural networks for Dynamic Initial Margin (DIM) computation in counterparty credit risk, a task traditionally burdened by the high costs associated with generating training datasets through nested
Externí odkaz:
http://arxiv.org/abs/2407.16435
In these notes we propose and analyze an inertial type method for obtaining stable approximate solutions to nonlinear ill-posed operator equations. The method is based on the Levenberg-Marquardt (LM) iteration. The main obtained results are: monotoni
Externí odkaz:
http://arxiv.org/abs/2406.07044
This paper addresses the problem of pricing involved financial derivatives by means of advanced of deep learning techniques. More precisely, we smartly combine several sophisticated neural network-based concepts like differential machine learning, Mo
Externí odkaz:
http://arxiv.org/abs/2404.11257
Autor:
West, Daniel J, Glang, Felix, Endres, Jonathan, Leitão, David, Zaiss, Moritz, Hajnal, Joseph V, Malik, Shaihan J
MRI systems are traditionally engineered to produce close to idealized performance, enabling a simplified pulse sequence design philosophy. An example of this is control of eddy currents produced by gradient fields; usually these are compensated by p
Externí odkaz:
http://arxiv.org/abs/2403.17575
Autor:
Alves, Jean V., Leitão, Diogo, Jesus, Sérgio, Sampaio, Marco O. P., Liébana, Javier, Saleiro, Pedro, Figueiredo, Mário A. T., Bizarro, Pedro
Learning to defer (L2D) aims to improve human-AI collaboration systems by learning how to defer decisions to humans when they are more likely to be correct than an ML classifier. Existing research in L2D overlooks key real-world aspects that impede i
Externí odkaz:
http://arxiv.org/abs/2403.06906
In this manuscript we propose and analyze an implicit two-point type method (or inertial method) for obtaining stable approximate solutions to linear ill-posed operator equations. The method is based on the iterated Tikhonov (iT) scheme. We establish
Externí odkaz:
http://arxiv.org/abs/2401.15213
Autor:
Alves, Jean V., Leitão, Diogo, Jesus, Sérgio, Sampaio, Marco O. P., Saleiro, Pedro, Figueiredo, Mário A. T., Bizarro, Pedro
Public dataset limitations have significantly hindered the development and benchmarking of learning to defer (L2D) algorithms, which aim to optimally combine human and AI capabilities in hybrid decision-making systems. In such systems, human availabi
Externí odkaz:
http://arxiv.org/abs/2312.13218