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Leticia Decker
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2020 – today
- 2022
- [j1]Leticia Decker, Daniel F. Leite, Francesco Minarini, Simone Rossi Tisbeni, Daniele Bonacorsi:
Unsupervised Learning and Online Anomaly Detection: An On-Condition Log-Based Maintenance System. Int. J. Embed. Real Time Commun. Syst. 13(1): 1-16 (2022) - [c4]Leticia Decker, Daniel F. Leite, Daniele Bonacorsi:
Explainable Log Parsing and Online Interval Granular Classification from Streams of Words. FUZZ-IEEE 2022: 1-8 - 2020
- [c3]Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi:
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. EAIS 2020: 1-8 - [c2]Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi:
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. FUZZ-IEEE 2020: 1-8 - [c1]Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza:
EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. FUZZ-IEEE 2020: 1-9 - [i3]Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza:
EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. CoRR abs/2004.09986 (2020) - [i2]Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi:
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. CoRR abs/2004.13527 (2020) - [i1]Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi:
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. CoRR abs/2005.04156 (2020)
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