Forecasting with twitter data M Arias, A Arratia, R Xuriguera ACM Transactions on Intelligent Systems and Technology (TIST) 5 (1), 1-24, 2014 | 278 | 2014 |
A deep-reinforcement learning approach for software-defined networking routing optimization G Stampa, M Arias, D Sánchez-Charles, V Muntés-Mulero, A Cabellos arXiv preprint arXiv:1709.07080, 2017 | 206 | 2017 |
Predicting electricity distribution feeder failures using machine learning susceptibility analysis P Gross, A Boulanger, M Arias, DL Waltz, PM Long, C Lawson, ... | 88 | 2006 |
An approach to software testing of machine learning applications C Murphy, GE Kaiser, M Arias | 87 | 2007 |
Compact routing with name independence M Arias, LJ Cowen, KA Laing, R Rajaraman, O Taka Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and …, 2003 | 81 | 2003 |
GeoSRS: A hybrid social recommender system for geolocated data J Capdevila, M Arias, A Arratia Information Systems 57, 111-128, 2016 | 64 | 2016 |
Real-time ranking with concept drift using expert advice H Becker, M Arias Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 44 | 2007 |
System and method for grading electricity distribution network feeders susceptible to impending failure RN Anderson, A Boulanger, DL Waltz, P Long, M Arias, P Gross, H Becker, ... US Patent 7,945,524, 2011 | 42 | 2011 |
Learning Horn Expressions with LOGAN-H. M Arias, R Khardon, J Maloberti Journal of Machine Learning Research 8 (3), 2007 | 37 | 2007 |
Construction and learnability of canonical Horn formulas M Arias, JL Balcázar Machine Learning 85 (3), 273-297, 2011 | 34 | 2011 |
Challenging the generalization capabilities of graph neural networks for network modeling J Suárez-Varela, S Carol-Bosch, K Rusek, P Almasan, M Arias, ... Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos, 114-115, 2019 | 31 | 2019 |
Learning closed Horn expressions M Arias, R Khardon Information and Computation 178 (1), 214-240, 2002 | 31 | 2002 |
Identifiability and transportability in dynamic causal networks G Blondel, M Arias, R Gavaldà International journal of data science and analytics 3 (2), 131-147, 2017 | 24 | 2017 |
Parameterizing random test data according to equivalence classes C Murphy, G Kaiser, M Arias Proceedings of the 2nd international workshop on Random testing: co-located …, 2007 | 22 | 2007 |
Learning regulatory programs that accurately predict differential expression with MEDUSA A Kundaje, S Lianoglou, X Li, D Quigley, M Arias, CH Wiggins, L Zhang, ... Annals of the New York Academy of Sciences 1115 (1), 178-202, 2007 | 19 | 2007 |
Introduction to Network Dynamics M Arias, R Ferrer-i-Cancho, A Arratia | 17 | 2020 |
Canonical Horn representations and query learning M Arias, JL Balcázar International Conference on Algorithmic Learning Theory, 156-170, 2009 | 15 | 2009 |
From training to match performance: a predictive and explanatory study on novel tracking data J Fernández, D Medina, A Gómez, M Arias, R Gavalda 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016 | 12 | 2016 |
A multi-scale smoothing kernel for measuring time-series similarity A Troncoso, M Arias, JC Riquelme Neurocomputing 167, 8-17, 2015 | 12 | 2015 |
Learning definite Horn formulas from closure queries M Arias, JL Balcázar, C Tîrnăucă Theoretical Computer Science 658, 346-356, 2017 | 10 | 2017 |