568 citations
- Institució Catalana de Recerca i Estudis AvançatsES41 papers
- Santa Fe InstituteUS15 papers
- Universitat Politècnica de CatalunyaES11 papers
- Barcelona Biomedical Research ParkES10 papers
- Institut de Biologia EvolutivaES7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Universitat de BarcelonaES6 papers
- Centre de Recerca MatemàticaES5 papers
- University of OxfordGB5 papers
- Institut national de recherche en sciences et technologies du numériqueFR4 papers
- McGill UniversityCA4 papers
- New York UniversityUS4 papers
19 papers · 1 filter
Online learning with noisy side observations
Tomáš Kocák, Gergely Neu, Michal Valko
We propose a new partial-observability model for online learning problems where the learner, besides its own loss, also observes some noisy feedback about the other actions, depend…
HAIDA: Biometric technological therapy tools for neurorehabilitation of Cognitive Impairment
Elsa Fernandez, Jordi Sole-Casals, Pilar M. Calvo +2
Dementia, and specially Alzheimer s disease (AD) and Mild Cognitive Impairment (MCI) are one of the most important diseases suffered by elderly population. Music therapy is one of…
A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation
Beatriz Cabrero Daniel, Ricardo Marques, Ludovic Hoyet +2
Simulating crowds requires controlling a very large number of trajectories and is usually performed using crowd motion algorithms for which appropriate parameter values need to be…
Learning Football Body-Orientation as a Matter of Classification
Adrià Arbués-Sangüesa, Adrián Martín, Paulino Granero +2
Orientation is a crucial skill for football players that becomes a differential factor in a large set of events, especially the ones involving passes. However, existing orientation…
Leveraging Good Representations in Linear Contextual Bandits
Matteo Papini, Andrea Tirinzoni, Marcello Restelli +2
The linear contextual bandit literature is mostly focused on the design of efficient learning algorithms for a given representation. However, a contextual bandit problem may admit…
Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
Marzieh Karimi-Haghighi, Carlos Castillo, Davinia Hernandez-Leo +1
In this work, the problem of predicting dropout risk in undergraduate studies is addressed from a perspective of algorithmic fairness. We develop a machine learning method to predi…