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Ricardo Vilalta
Ricardo Vilalta
University of Austin
Verified email at ieee.org - Homepage
Title
Cited by
Cited by
Year
A perspective view and survey of meta-learning
R Vilalta, Y Drissi
Artificial intelligence review 18, 77-95, 2002
15882002
Metalearning: Applications to data mining
P Brazdil, CG Carrier, C Soares, R Vilalta
Springer Science & Business Media, 2008
9192008
Critical event prediction for proactive management in large-scale computer clusters
RK Sahoo, AJ Oliner, I Rish, M Gupta, JE Moreira, S Ma, R Vilalta, ...
Proceedings of the ninth ACM SIGKDD international conference on Knowledge …, 2003
3892003
Predicting rare events in temporal domains
R Vilalta, S Ma
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 474-481, 2002
2482002
Introduction to the special issue on meta-learning
C Giraud-Carrier, R Vilalta, P Brazdil
Machine learning 54, 187-193, 2004
2322004
Predictive algorithms in the management of computer systems
R Vilalta, CV Apte, JL Hellerstein, S Ma, SM Weiss
IBM Systems Journal 41 (3), 461-474, 2002
1642002
Using Meta-Learning to Support Data Mining.
R Vilalta, CG Giraud-Carrier, P Brazdil, C Soares
Int. J. Comput. Sci. Appl. 1 (1), 31-45, 2004
1592004
The dark machines anomaly score challenge: benchmark data and model independent event classification for the large hadron collider
T Aarrestad, M van Beekveld, M Bona, A Boveia, S Caron, J Davies, ...
SciPost Physics 12 (1), 043, 2022
1002022
Meta-learning-concepts and techniques
R Vilalta, C Giraud-Carrier, P Brazdil
Data mining and knowledge discovery handbook, 717-731, 2010
962010
Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning
EEO Ishida, R Beck, S González-Gaitán, RS de Souza, A Krone-Martins, ...
Monthly Notices of the Royal Astronomical Society 483 (1), 2-18, 2019
832019
Supervised learning to detect salt body
P Guillen, G Larrazabal, G González, D Boumber, R Vilalta
SEG International Exposition and Annual Meeting, SEG-2015-5931401, 2015
762015
A decomposition of classes via clustering to explain and improve naive bayes
R Vilalta, I Rish
Machine Learning: ECML 2003: 14th European Conference on Machine Learning …, 2003
702003
Method and system for predicting a drill string stuck pipe event
T Goebel, RV Molina, R Vilalta, KD Gupta
US Patent 8,752,648, 2014
692014
Applications and techniques for fast machine learning in science
AMC Deiana, N Tran, J Agar, M Blott, G Di Guglielmo, J Duarte, P Harris, ...
Frontiers in big Data 5, 787421, 2022
662022
Detecting impact craters in planetary images using machine learning
TF Stepinski, W Ding, R Vilalta
Intelligent data analysis for real-life applications: Theory and practice …, 2012
652012
Disk failure prediction in heterogeneous environments
CAC Rincón, JF Pâris, R Vilalta, AMK Cheng, DDE Long
2017 International Symposium on Performance Evaluation of Computer and …, 2017
642017
Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining
G Toti, R Vilalta, P Lindner, B Lefer, C Macias, D Price
Artificial intelligence in medicine 74, 44-52, 2016
582016
Probing the fundamental nature of dark matter with the large synoptic survey telescope
A Drlica-Wagner, YY Mao, S Adhikari, R Armstrong, A Banerjee, N Banik, ...
arXiv preprint arXiv:1902.01055, 2019
562019
Using representative-based clustering for nearest neighbor dataset editing
CF Eick, N Zeidat, R Vilalta
Fourth IEEE International Conference on Data Mining (ICDM'04), 375-378, 2004
502004
Class decomposition via clustering: a new framework for low-variance classifiers
R Vilalta, MK Achari, CF Eick
Third IEEE International Conference on Data Mining, 673-676, 2003
472003
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