Learning Systems

The research of this group focuses on the development of machine learning algorithms, models, software and applications. From an algorithmic/modeling perspective, the group pursues research in Probabilittic Graphical Models,  Case-Base Reasoning, Transfer Learning, and Deep Learning. From the software and applications perspective the group concentrates on the application areas such as Social Networks, Music, Robotics, Multiagent Systems, Bioinformatics, and Healthcare.

Head of Department:  Josep Lluís Arcos
Josep Lluís Arcos
Scientific Researcher
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Eva Armengol
Tenured Scientist
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Xavier Carreras
Tenured Scientist
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Jesus Cerquides
Scientific Researcher
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Núria Correa
Industrial PhD Student
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Jose Luis Fernandez Marquez
Visiting Scientist
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Ramon Lopez de Mantaras
Research Professor
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Oguz Mulayim
Contract Researcher
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Enric Plaza
Research Professor
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Guillermo H. Rodríguez
Visiting Scientist
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Borja Sánchez-López
PhD Student
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Kian Seif
PhD Student

Borja Velasco
PhD Student

In Press
Emma Segura,  Jennifer Grau-Sánchez,  David Sanchez-Pinsach,  Myriam De-la-Cruz,  Esther Duarte,  Josep Lluis Arcos,  & Antoni Rodríguez-Fornells (In Press). Designing an app for home-based enriched Music-supported Therapy in the rehabilitation of patients with chronic stroke: a pilot feasibility study. Brain Injury. [BibTeX]
2021
Dimitra Bourou,  Marco Schorlemmer,  & Enric Plaza (2021). A Cognitively-Inspired Model for Making Sense of Hasse Diagrams. Proc. of the 23rd International Conference of the Catalan Association for Artificial Intelligence (CCIA 2021), October 20-22, Lleida, Catalonia, Spain . [BibTeX]
Filippo Bistaffa,  Christian Blum,  Jesús Cerquides,  Alessandro Farinelli,  & Juan A. Rodríguez-Aguilar (2021). A Computational Approach to Quantify the Benefits of Ridesharing for Policy Makers and Travellers. IEEE Transactions on Intelligent Transportation Systems, 22, 119-130. https://doi.org/10.1109/TITS.2019.2954982. [BibTeX]  [PDF]
Jesus Cerquides,  Oguz Mulayim,  Jerónimo Hernández-González,  Amudha Ravi Shankar,  & Jose Luis Fernandez-Marquez (2021). A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data. Mathematics, 9. https://doi.org/10.3390/math9080875. [BibTeX]  [PDF]
Marco Schorlemmer,  & Enric Plaza (2021). A Uniform Model of Computational Conceptual Blending. Cognitive Systems Research, 65, 118--137. https://doi.org/10.1016/j.cogsys.2020.10.003. [BibTeX]  [PDF]
Núria Correa,  Jesús Cerquides,  Josep Lluis Arcos,  & Rita Vassena (2021). Development and validation of an Artificial Intelligence algorithm that matches a clinician ability to select the best follitropin dose for ovarian stimulation. ESHRE . [BibTeX]
Borja Sánchez-López,  & Jesus Cerquides (2021). Dual Stochastic Natural Gradient Descent and convergence of interior half-space gradient approximations. [BibTeX]  [PDF]
Jennifer Grau-Sánchez,  Emma Segura,  David Sanchez-Pinsach,  Preeti Raghavan,  Thomas F. Münte,  Anna Marie Palumbo,  Alan Turry,  Esther Duarte,  Särkämö Särkämö,  Jesus Cerquides,  Josep Lluis Arcos,  & Antoni Rodriguez-Fornells (2021). Enriched Music-supported Therapy for chronic stroke patients: a study protocol of a randomised controlled trial. BMC Neurology, 21. https://doi.org/10.1186/s12883-020-02019-1. [BibTeX]  [PDF]
Emma Segura,  Jennifer Grau-Sánchez,  David Sanchez-Pinsach,  Esther Duarte,  Josep Lluis Arcos,  & Antoni Rodríguez-Fornells (2021). Enriched music-supported therapy in the improvement of motor function and quality of life of chronic stroke patients: a pilot study. NeuroMusic VII . [BibTeX]
Dimitra Bourou,  Marco Schorlemmer,  & Enric Plaza (2021). Image Schemas in Diagrammatic Reasoning: the Case of Hasse Diagrams. Proc. of the 12th Int. Conf. on the Theory and Application of Diagrams (Diagrams 2021), September 28--30 2021 . [BibTeX]
Núria Correa,  Rita Vassena,  Jesus Cerquides,  & Josep Lluis Arcos (2021). Limits of conventional Machine Learning methods to predict pregnancy and multiple pregnancy after embryo transfer. Ada Valls, & Mateu Villaret (Eds.), Frontiers in Artificial Intelligence and Applications (pp In Press). IOS Press. [BibTeX]
Dimitra Bourou,  Marco Schorlemmer,  & Enric Plaza (2021). Modelling the Sense-Making of Diagrams Using Image Schemas. Proc. of the 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), 26--29 July 2021, Vienna, Austria (pp. 1105-1111). [BibTeX]  [PDF]
Borja Sánchez-López,  & Jesus Cerquides (2021). On the Convergence of Stochastic Process Convergence Proofs. Mathematics, 9. https://doi.org/10.3390/math9131470. [BibTeX]  [PDF]
Borja Sánchez-López,  & Jesus Cerquides (2021). On the Convergence of Stochastic Process Convergence Proofs. Mathematics, 9. https://doi.org/10.3390/math9131470. [BibTeX]  [PDF]
Jon Perez,  Jose Luis Flores,  Christian Blum,  Jesus Cerquides,  & Alex Abuin (2021). Optimization Techniques and Formal Verification for the Software Design of Boolean Algebra Based Safety-Critical Systems. IEEE Transactions on Industrial Informatics, 1-1. https://doi.org/10.1109/TII.2021.3074394. [BibTeX]
Jesus Cerquides (2021). Parametrization invariant interpretation of priors and posteriors. arXiv:2105.08304 [cs, math, stat]. https://doi.org/http://arxiv.org/abs/2105.08304. [BibTeX]
Jesús Cerquides,  Juan A. Rodríguez-Aguilar,  Rémi Emonet,  & Gauthier Picard (2021). Solving Highly Cyclic Distributed Optimization Problems Without Busting the Bank: A Decimation-based Approach. Logic Journal of the IGPL, 29, 72-95. https://doi.org/10.1093/jigpal/jzaa069. [BibTeX]
2020
Jerónimo Hernández-González,  & Jesús Cerquides (2020). A Robust Solution to Variational Importance Sampling of Minimum Variance. Entropy, 22, 1405. https://doi.org/10.3390/e22121405. [BibTeX]  [PDF]
Eva Armengol,  & {\`{A}}ngel Garc{í}a{-}Cerda{\~{n}}a (2020). Decision Trees as a Tool for Data Analysis. Elections in Barcelona: A Case Study. Vicen{\\c{c}}Torra, Yasuo Narukawa, Jordi Nin, & N{\\'{u}}ria Agell (Eds.), Modeling Decisions for Artificial Intelligence - 17th International Conference, {MDAI}2020, Sant Cugat, Spain, September 2-4, 2020, Proceedings (pp. 261--272). Springer. https://doi.org/10.1007/978-3-030-57524-3\_22. [BibTeX]  [PDF]
Oguz Mulayim,  & Josep Lluis Arcos (2020). Fast anytime retrieval with confidence in large-scale temporal case bases. Knowledge-Based Systems, 206, 106374. https://doi.org/10.1016/j.knosys.2020.106374. [BibTeX]