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pro vyhledávání: '"Marin, Ignacio"'
We present our solution for the M5 Forecasting - Uncertainty competition. Our solution ranked 6\ts{th} out of 909 submissions across all hierarchical levels and ranked first for prediction at the finest level of granularity (product-store sales, i.e.
Externí odkaz:
http://arxiv.org/abs/2111.14721
Publikováno v:
In International Journal of Forecasting October-December 2022 38(4):1460-1467
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
Bioinformatics 30, 1041 (2014)
Detecting communities, densely connected groups may contribute to unravel the underlying relationships among the units present in diverse biological networks (e.g., interactome, coexpression networks, ecological networks, etc.). We recently showed th
Externí odkaz:
http://arxiv.org/abs/1310.2357
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
Scientific Reports 3, 2216 (2013)
The characterization of network community structure has profound implications in several scientific areas. Therefore, testing the algorithms developed to establish the optimal division of a network into communities is a fundamental problem in the fie
Externí odkaz:
http://arxiv.org/abs/1306.4149
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
Scientific Reports 3, 1060 (2013)
How to determine the community structure of complex networks is an open question. It is critical to establish the best strategies for community detection in networks of unknown structure. Here, using standard synthetic benchmarks, we show that none o
Externí odkaz:
http://arxiv.org/abs/1301.0239
Autor:
Cabré, Eduard, Mañosa, Míriam, Marín, Ignacio, Martín-Mateos, Rosa, Iglesias-Flores, Eva, Barreiro-de-Acosta, Manuel, Nos, Pilar, Busquets, David, Menchén, Luis A., López-Sanromán, Antonio, Domènech, Eugeni
Publikováno v:
In Digestive and Liver Disease May 2019 51(5):669-674
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
PLoS ONE 5(7): e11585 (2010)
Background: How to extract useful information from complex biological networks is a major goal in many fields, especially in genomics and proteomics. We have shown in several works that iterative hierarchical clustering, as implemented in the UVClust
Externí odkaz:
http://arxiv.org/abs/1204.4584
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
Phys. Rev. E 85, 026109 (2012)
Characterizing the community structure of complex networks is a key challenge in many scientific fields. Very diverse algorithms and methods have been proposed to this end, many working reasonably well in specific situations. However, no consensus ha
Externí odkaz:
http://arxiv.org/abs/1202.5909
Autor:
Aldecoa, Rodrigo, Marín, Ignacio
Publikováno v:
PLoS ONE 6(9): e24195 (2011)
The analysis of complex networks permeates all sciences, from biology to sociology. A fundamental, unsolved problem is how to characterize the community structure of a network. Here, using both standard and novel benchmarks, we show that maximization
Externí odkaz:
http://arxiv.org/abs/1105.2459
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