Miquel Perelló-Nieto

According to our database, Miquel Perelló-Nieto authored at least 20 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exploring the Requirements of Clinicians for Explainable AI Decision Support Systems in Intensive Care.

Jeffrey N. Clark, Matthew Wragg, Emily Nielsen, Miquel Perelló-Nieto, Nawid Keshtmand, Michael Ambler, Shiv Sharma, Christopher P. Bourdeaux, Amberly Brigden, Raúl Santos-Rodríguez

CoRR, 2024

Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions.

Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

An active semi-supervised deep learning model for human activity recognition.

Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach, Ian Craddock

J. Ambient Intell. Humaniz. Comput., October, 2023

Classifier calibration: a survey on how to assess and improve predicted class probabilities.

Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach

Mach. Learn., September, 2023

When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations.

Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

2022

The Weak Supervision Landscape.

Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez

Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

2021

Human Activity Recognition Based on Dynamic Active Learning.

Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach

IEEE J. Biomed. Health Informatics, 2021

Classifier Calibration: How to assess and improve predicted class probabilities: a survey.

Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach

CoRR, 2021

Data labelling in the wild: annotating free-living activities and Parkinson's disease symptoms.

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

Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2021

On the Selection of Loss Functions Under Known Weak Label Models.

Daniel Bacaicoa-Barber, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery.

Michael Holmes, Miquel Perelló-Nieto, Hao Song, Emma Tonkin, Sabrina Grant, Peter A. Flach

J. Heal. Informatics Res., 2020

Recycling weak labels for multiclass classification.

Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Dario García-García, Jesús Cid-Sueiro

Neurocomputing, 2020

Towards a Methodology for Acceptance Testing and Validation of Monitoring Bodyworn Devices.

Emma L. Tonkin, Miquel Perelló-Nieto, Haixia Bi, Antonis Vafeas

Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, 2020

2019

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.

Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach

CoRR, 2019

HyperStream: a Workflow Engine for Streaming Data.

Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perelló-Nieto, Emma Tonkin, Peter A. Flach

CoRR, 2019

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration.

Meelis Kull, Miquel Perelló-Nieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.

Tom Diethe, Mike Holmes, Meelis Kull, Miquel Perelló-Nieto, Kacper Sokol, Hao Song, Emma Tonkin, Niall Twomey, Peter A. Flach

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild.

Mike Holmes, Hao Song, Emma Tonkin, Miquel Perelló-Nieto, Sabrina Grant, Peter A. Flach

Proceedings of the 3rd International Workshop on Knowledge Discovery in Healthcare Data co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), 2018

2017

Adapting Supervised Classification Algorithms to Arbitrary Weak Label Scenarios.

Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro

Proceedings of the Advances in Intelligent Data Analysis XVI, 2017

2016

Background Check: A General Technique to Build More Reliable and Versatile Classifiers.

Miquel Perelló-Nieto, Telmo de Menezes e Silva Filho, Meelis Kull, Peter A. Flach

Proceedings of the IEEE 16th International Conference on Data Mining, 2016