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ORCIDMiquel Perelló-Nieto
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2020 – today
- 2024
[c11]Paul-Gauthier Noé
, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach:
Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions. ECAI 2024: 1124-1131- [i6]Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach:
Explaining a probabilistic prediction on the simplex with Shapley compositions. CoRR abs/2408.01382 (2024) - 2023
- [j5]Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach, Ian Craddock:
An active semi-supervised deep learning model for human activity recognition. J. Ambient Intell. Humaniz. Comput. 14(10): 13049-13065 (2023) - [j4]Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach:
Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. 112(9): 3211-3260 (2023) - [c10]Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach:
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. PerCom Workshops 2023: 527-533 - [i5]Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach:
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. CoRR abs/2302.02706 (2023) - 2022
- [c9]Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez:
The Weak Supervision Landscape. PerCom Workshops 2022: 218-223 - [i4]Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez:
The Weak Supervision Landscape. CoRR abs/2203.16282 (2022) - 2021
- [j3]Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach:
Human Activity Recognition Based on Dynamic Active Learning. IEEE J. Biomed. Health Informatics 25(4): 922-934 (2021) - [c8]Daniel Bacaicoa-Barber, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro:
On the Selection of Loss Functions Under Known Weak Label Models. ICANN (2) 2021: 332-343 - [c7]Catherine Morgan, Farnoosh Heidarivincheh, Ian Craddock, Ryan McConville, Miquel Perelló-Nieto, Emma L. Tonkin, Alessandro Masullo, Antonis Vafeas, Mickey Kim, Roisin McNaney, Gregory J. L. Tourte, Alan L. Whone:
Data labelling in the wild: annotating free-living activities and Parkinson's disease symptoms. PerCom Workshops 2021: 471-474 - [i3]Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach:
Classifier Calibration: How to assess and improve predicted class probabilities: a survey. CoRR abs/2112.10327 (2021) - 2020
- [j2]Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Dario García-García, Jesús Cid-Sueiro:
Recycling weak labels for multiclass classification. Neurocomputing 400: 206-215 (2020) - [j1]Michael Holmes, Miquel Perelló-Nieto, Hao Song, Emma Tonkin, Sabrina Grant, Peter A. Flach:
Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery. J. Heal. Informatics Res. 4(3): 238-260 (2020) - [c6]Emma L. Tonkin, Miquel Perelló-Nieto, Haixia Bi, Antonis Vafeas:
Towards a Methodology for Acceptance Testing and Validation of Monitoring Bodyworn Devices. PerCom Workshops 2020: 1-6
2010 – 2019
- 2019
- [c5]Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach:
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. NeurIPS 2019: 12295-12305 - [i2]Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach:
HyperStream: a Workflow Engine for Streaming Data. CoRR abs/1908.02858 (2019) - [i1]Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach:
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. CoRR abs/1910.12656 (2019) - 2018
- [c4]Mike Holmes, Hao Song, Emma Tonkin, Miquel Perelló-Nieto, Sabrina Grant, Peter A. Flach:
Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild. KDH@IJCAI 2018: 13-20 - [c3]Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach:
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. KDD 2018: 243-252 - 2017
- [c2]Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro:
Adapting Supervised Classification Algorithms to Arbitrary Weak Label Scenarios. IDA 2017: 247-259 - 2016
- [c1]Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach:
Background Check: A General Technique to Build More Reliable and Versatile Classifiers. ICDM 2016: 1143-1148
Coauthor Index
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