Zobrazeno 1 - 10
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pro vyhledávání: '"Vilar, José"'
Autor:
Vilar, Jose M. G.
The efficient market hypothesis considers all available information already reflected in asset prices and limits the possibility of consistently achieving above-average returns by trading on publicly available data. We analyzed low dispersion predict
Externí odkaz:
http://arxiv.org/abs/2410.08009
Autor:
Ismail, Shahid, Diaz, Moises, Carmona-Duarte, Cristina, Vilar, Jose Manuel, Ferrer, Miguel A.
Publikováno v:
Computers and Electronics in Agriculture, vol.216, pp.108500, 2024
Lameness is one of the costliest pathological problems affecting dairy animals. It is usually assessed by trained veterinary clinicians who observe features such as gait symmetry or gait parameters as step counts in real-time. With the development of
Externí odkaz:
http://arxiv.org/abs/2405.15550
Autor:
Vilar, Jose M. G., Saiz, Leonor
Continuous adaptation to variable environments is crucial for the survival of living organisms. Here, we analyze how adaptation, forecasting, and resource mobilization towards a target state, termed actionability, interact to determine biological fun
Externí odkaz:
http://arxiv.org/abs/2404.07895
Time series clustering is a central machine learning task with applications in many fields. While the majority of the methods focus on real-valued time series, very few works consider series with discrete response. In this paper, the problem of clust
Externí odkaz:
http://arxiv.org/abs/2304.12249
Autor:
Andrés-Esperanza, Javier1 (AUTHOR) fandres@uji.es, Iserte-Vilar, José L.1 (AUTHOR), Roda-Casanova, Víctor1 (AUTHOR)
Publikováno v:
Biomimetics (2313-7673). Oct2024, Vol. 9 Issue 10, p616. 24p.
Autor:
Vilar, Jose M. G., Saiz, Leonor
Publikováno v:
Science Advances 9, eadf0673 (2023)
Inferring the timing and amplitude of perturbations in epidemiological systems from their stochastically spread low-resolution outcomes is as relevant as challenging. It is a requirement for current approaches to overcome the need to know the details
Externí odkaz:
http://arxiv.org/abs/2209.07802
Three robust methods for clustering multivariate time series from the point of view of generating processes are proposed. The procedures are robust versions of a fuzzy C-means model based on: (i) estimates of the quantile cross-spectral density and (
Externí odkaz:
http://arxiv.org/abs/2109.11027
A novel procedure to perform fuzzy clustering of multivariate time series generated from different dependence models is proposed. Different amounts of dissimilarity between the generating models or changes on the dynamic behaviours over time are some
Externí odkaz:
http://arxiv.org/abs/2109.03728
Autor:
López-Oriona, Ángel, Vilar, José A.
Publikováno v:
In Journal of Computational Science March 2024 76