2021
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Sketches for Time-Dependent Machine Learning.
J. Antonanzas, M. Arias, A. Bifet. [arXiv preprint]
2020
2019
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Synthetic Dataset Generation with Itemset-Based Generative Models.
C. Lezcano, M. Arias.
IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW@RDSA 2019), Oct 2019.
[arXiv preprint]
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Challenging the generalization capabilities of Graph Neural Networks for network modeling.
J. Suárez-Varela, S. Carol-Bosch, K. Rusek, P. Almasan, M. Arias, P. Barlet-Ros, A. Cabellos-Aparicio.
ACM SIGCOMM Conference Posters and Demos, August 2019.
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Characterizing Transactional Databases for Frequent Itemset Mining.
C. Lezcano, M. Arias.
Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML@SDM 2019), May 2019.
[arXiv preprint]
2017
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A Deep-Reinforcement Learning Approach for Software-Defined Networking Routing Optimization.
G. Stampa, M. Arias, D. Sanchez-Charles, V. Muntes-Mulero, A. Cabellos.
The ACM CoNEXT 2017 Student Workshop, Dec. 2017. [arXiv preprint]
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Classifier selection with permutation tests.
M. Arias, A. Arratia, A. Duarte-López.
20th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2017), Oct. 2017.
[arXiv preprint]
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Better Match Physical Performance Achieved in Professional Football with Higher Variability During Training: A Machine-Learning Approach.
J. Fernández, D. Medina, A. Gómez, M. Arias, R. Gavaldà.
Book of Abstracts of the 22nd Annual Congress of the European College of Sport Science, Jul. 2017.
Placed 3rd in the Excellence in Football Research Award.
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Does like seek like?: The formation of working groups in a programming project.
E. Sanou-Gozalo, A. Hernandez-Fernandez, M. Arias, R. Ferrer-i-Cancho.
Journal of Technology and Science Education (JOTSE), Vol 7, No 2, 2017, pp 231-240.
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Learning Definite Horn Formulas from Closure Queries.
M. Arias, J.L. Balcazar, C. Tirnauca.
Special Issue on Horn Formulas, Directed Hypergraphs and Closure Systems.
Theoretical Computer Science (TCS), Vol 658, Part B, Jan 2017, pp 346–356.
[arXiv preprint]
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Identifiability and Transportability in Dynamic Causal Networks.
G. Blondel, M. Arias, R. Gavaldà.
Special Issue on Causal Discovery. International Journal of Data Science and Analytics, 3(2), 2017, pp 131-147.
2016
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Identifiability and Transportability in Dynamic Causal Networks.
G. Blondel, M. Arias, R. Gavaldà.
The 2016 ACM SIGKDD Workshop on Causal Discovery, held in conjunction with KDD 2016.
[talk, pdf, slides]
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From Training to Match Performance: A Predictive and Explanatory Study on Novel Tracking Data.
J. Fernández, D. Medina, A. Gómez, M. Arias, R. Gavaldà.
Workshop on Data mining for the Analysis of Performance and Success, held in conjunction with ICDM 2016.
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Automated Construction and Analysis of Political Networks via open government and media sources.
D. García-Olano, M. Arias, J.L. Larriba-Pey.
Workshop on Data Science for Social Good (SoGood 2016), associated to ECML PKDD 2016. [slides]
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Does Training Affect Match Performance? A Study Using Data Mining And Tracking Devices.
J. Fernández, D. Medina, A. Gómez, M. Arias, R. Gavaldà.
Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 16), associated to ECML PKDD 2016. [slides]
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GeoSRS: A Hybrid Social Recommender System for Geolocated Data.
J. Capdevila-Pujol, M. Arias, A. Arratia.
Special Issue on Mining Urban Data.
Information Systems, Vol 57, Apr 2016, pp. 111--128.
2015
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Characterizing Chronic Disease and Polymedication Prescription Patterns from Electronic Health Records.
M. Zamora, M. Baradad, E. Amado, S. Cordomí, E. Limón, J. Ribera, M. Arias, R. Gavaldà.
2015 IEEE International Conference on Data Science and Advanced Analytics, Oct. 2015.
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A multi-scale smoothing kernel for measuring time-series similarity.
M. Arias, A. Troncoso, J. Riquelme.
Neurocomputing, Vol 167, Nov 2015, pp. 8--17.
2013
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Forecasting with Twitter Data.
M. Arias, A. Arratia, R. Xuriguera.
Special Issue on Social Web Mining.
ACM Transactions on Intelligent Systems and Technology (TIST), Vol 5 (1), December 2013.
2012
2011
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Forecasting financial time series with Twitter. [abstract]
R. Xuriguera, M. Arias, A. Arratia.
4th International Conference of the European Research Consortium for Informatics and Mathematics
Working Group on Computing & Statistics (ERCIM 2011), Dec 2011.
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Construction and learnability of canonical Horn formulas.
M. Arias, J.L. Balcázar.
Machine Learning Journal, Vol. 85 (3), Oct 2011, pp. 273-297.
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Learning Theory through Videos - A Teaching Experience in a Theoretical Course based on Self-learning Videos and Problem-solving Sessions.
M. Arias, C. Creus, A. Gascón, G. Godoy.
International Conference on Computer Supported Education (2), May 2011: 93-98.
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Structured-Content Extraction from the Web for Bibliographic Reference Generation
R. Xuriguera, M. Arias.
RFIW Atelier (within EGC 2011), Jan 2011.
2010
2009
2008
2007
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Learning regulatory programs that accurately predict differential expression with MEDUSA.
A. Kundaje, S. Lianoglou, X. Li, D. Quigley, M. Arias, C. Wiggins, L. Zhang, C. Leslie.
Annals of the New York Academy of Science, Volume 1115, Dec 2007, pp. 178-202.
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Parameterizing Random Test Data According to Equivalence Classes.
C. Murphy, G. Kaiser, M. Arias.
Second International Workshop on Random Testing 2007, Nov 2007.
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Real-time Ranking with Concept Drift Using Expert Advice.
H. Becker, M. Arias.
KDD 2007, Aug 2007.
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An Approach to Software Testing of Machine Learning Applications.
C. Murphy, G. Kaiser, M. Arias.
SEKE 2007, Jul 2007.
- Learning Horn Expressions with LogAn-H.
M. Arias, R. Khardon, J. Maloberti.
Journal of Machine Learning Research, Vol. 8, Mar 2007, pp. 549-587.
- Real-time Ranking of Electrical Feeders using Expert Advice.
H. Becker, M. Arias.
European Workshop on Data Stream Analysis, Mar 2007, Caserta, Italy.
2006
- An Online Learning System for the Prediction of Electricity Distribution Feeder Failures.
H. Becker, M. Arias.
- New York Academy of Sciences Machine Learning Symposium, Oct 2006. [abstract, 2-min presentation]
- Workshop in Machine Learning, Grace Hopper Celebration of Women in Computing, Oct 2006. [abstract, poster]
- Compact Routing with Name Idependence.
M. Arias, L. Cowen, K. Laing, R. Rajaraman, O. Taka.
SIAM Journal on Discrete Mathematics, Vol. 20 (3), Sep 2006, pp. 705-726.
- A Framework for Quality Assurance of Machine Learning Applications.
C. Murphy, G. Kaiser, M. Arias.
Tech Report, CUCS-034-06, Computer Science, Columbia University. Sep 2006.
- Learning regulatory programs that accurately predict differential expression with MEDUSA.
A. Kundaje, D. Quigley, S. Lianoglou, X. Li, M. Arias, C. Wiggins, L. Zhang, C. Leslie.
DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 2006.
- Complexity Parameters for First Order Classes.
M. Arias, R. Khardon.
Machine Learning Journal, Vol. 64 (1-3), Sep 2006, pp. 121-144.
- Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis.
P. Gross, A. Boulanger, M. Arias, D. L. Waltz, P. M. Long, C. Lawson, R. Anderson, M. Koenig,
M. Mastrocinque, W. Fairechio, J. A. Johnson, S. Lee, F. Doherty, A. Kressner.
AAAI 2006, Jul 2006.
- Polynomial Certificates for Propositional Classes.
M. Arias, A. Feigelson, R. Khardon, R. Servedio.
Information and Computation, Vol. 204 (5), May 2006, pp. 816-834. Attention: published version contains an
error in the order of the references; corrected un-official version here.
- The Subsumption Lattice and Query Learning.
R. Khardon, M. Arias.
Journal of Computer and System Sciences, Vol. 72 (1), Feb 2006, pp. 72-94.
2004
2003
- Complexity Parameters for First Order Classes.
M. Arias, R. Khardon.
ILP 2003, Oct 2003.
- Polynomial Certificates for Propositional Classes.
M. Arias, R. Khardon, R. Servedio.
COLT 2003, Aug 2003.
- Compact Roundtrip Routing with Topology-Independent Node Names.
M. Arias, L. Cowen, K. Laing.
PODC 2003, Jul 2003.
- Compact Routing with Name Independence.
M. Arias, L. Cowen, K. Laing, R. Rajaraman, O. Taka.
SPAA 2003, Jun 2003.
2002
2001
- Learning Closed Horn Expressions.
M. Arias, R. Khardon.
Workshop on Logic and Learning, IEEE Symposium on Logic in Computer Science (LICS), June 2001.
2000
- A New Algorithm for Learning Range Restricted Horn Expressions.
M. Arias, R. Khardon.
ILP 2000, Jul 2000.
- Learning Inequated Range Restricted Horn Expressions.
M. Arias, R. Khardon.
Research Report, EDI-INF-RR-0011, Division of Informatics, University of Edinburgh, Mar 2000.
- A New Algorithm for Learning Range Restricted Horn Expressions.
M. Arias, R. Khardon.
Research Report, EDI-INF-RR-0010, Division of Informatics, University of Edinburgh, Mar 2000.