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Borja R. Lafuente-Rego

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2020 – today

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2022
[j4]
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  - journals/ijar/Lopez-OrionaDVL22
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Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar, Borja R. Lafuente-Rego:
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques. Int. J. Approx. Reason. 150: 55-82 (2022)
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Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar, Borja R. Lafuente-Rego:
Spatial Weighted Robust Clustering of Multivariate Time Series Based on Quantile Dependence With an Application to Mobility During COVID-19 Pandemic. IEEE Trans. Fuzzy Syst. 30(9): 3990-4004 (2022)
2021
[c3]
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Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar, Borja R. Lafuente-Rego:
Spatial weighted robust clustering of multivariate time series based on quantile dependence with an application to mobility during COVID-19 pandemic. WILF 2021
[i1]
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  - journals/corr/abs-2109-11027
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Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar, Borja R. Lafuente-Rego:
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques. CoRR abs/2109.11027 (2021)

2010 – 2019

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2018
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José Antonio Vilar, Borja R. Lafuente-Rego, Pierpaolo D'Urso:
Quantile autocovariances: A powerful tool for hard and soft partitional clustering of time series. Fuzzy Sets Syst. 340: 38-72 (2018)
2016
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Borja R. Lafuente-Rego, José Antonio Vilar:
Clustering of time series using quantile autocovariances. Adv. Data Anal. Classif. 10(3): 391-415 (2016)
2015
[c2]
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Borja R. Lafuente-Rego, José Antonio Vilar:
Fuzzy Clustering of Series Using Quantile Autocovariances. AALTD@PKDD/ECML 2015
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Borja R. Lafuente-Rego, José Antonio Vilar:
Fuzzy Clustering of Series Using Quantile Autocovariances. AALTD@PKDD/ECML (Revised Selected Papers) 2015: 49-64

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