| A perspective view and survey of meta-learning R Vilalta, Y Drissi Artificial intelligence review 18, 77-95, 2002 | 1601 | 2002 |
| Metalearning: Applications to data mining P Brazdil, CG Carrier, C Soares, R Vilalta Springer science & business media, 2008 | 925 | 2008 |
| 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 | 385 | 2003 |
| Predicting rare events in temporal domains R Vilalta, S Ma 2002 IEEE International Conference on Data Mining, 2002. Proceedings., 474-481, 2002 | 249 | 2002 |
| Introduction to the special issue on meta-learning C Giraud-Carrier, R Vilalta, P Brazdil Machine learning 54, 187-193, 2004 | 235 | 2004 |
| 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 | 161 | 2002 |
| 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 | 160 | 2004 |
| 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 | 106 | 2022 |
| Meta-learning-concepts and techniques R Vilalta, C Giraud-Carrier, P Brazdil Data mining and knowledge discovery handbook, 717-731, 2010 | 96 | 2010 |
| 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 | 83 | 2019 |
| 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 | 76 | 2015 |
| 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 | 71 | 2022 |
| 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 | 70 | 2012 |
| 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 | 69 | 2014 |
| 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 | 69 | 2003 |
| 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 | 64 | 2017 |
| 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 | 60 | 2016 |
| 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 | 58 | 2019 |
| A probabilistic approach to emission-line galaxy classification RS De Souza, MLL Dantas, MV Costa-Duarte, ED Feigelson, M Killedar, ... Monthly Notices of the Royal Astronomical Society 472 (3), 2808-2822, 2017 | 48 | 2017 |
| 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 | 48 | 2004 |
Carlos SoaresAssociate Professor, Faculdade de Engenharia da U. Porto/External Advisor at Fraunhofer AICOSVerified email at fe.up.pt
