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ORCIDRafael Poyiadzi
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2020 – today
- 2024
[c10]Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez:
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. AAAI 2024: 21744-21752- [i14]William James Bolton, Rafael Poyiadzi, Edward R. Morrell, Gabriela van Bergen Gonzalez Bueno, Lea Goetz:
RAmBLA: A Framework for Evaluating the Reliability of LLMs as Assistants in the Biomedical Domain. CoRR abs/2403.14578 (2024) - 2023
- [i13]Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez:
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. CoRR abs/2312.10238 (2023) - 2022
- [c9]Niall Twomey, Sarah McMullan, Anat Elhalal, Rafael Poyiadzi, Luis M. Vaquero:
Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models. EDM 2022 - [c8]Jonas Schulz, Raúl Santos-Rodríguez, Rafael Poyiadzi:
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach. NLDL 2022 - [c7]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 - [c6]Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez:
Hypothesis Testing for Class-Conditional Label Noise. ECML/PKDD (3) 2022: 171-186 - [p1]Weisong Yang, Rafael Poyiadzi, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey:
Detecting and Monitoring Behavioural Patterns in Individuals with Cognitive Disorders in the Home Environment with Partial Annotations. Integrating Artificial Intelligence and IoT for Advanced Health Informatics 2022: 25-52 - [i12]Niall Twomey, Sarah McMullan, Anat Elhalal, Rafael Poyiadzi, Luis Miguel Vaquero:
Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models. CoRR abs/2203.10170 (2022) - [i11]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) - [i10]Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach:
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. CoRR abs/2209.03805 (2022) - 2021
- [i9]Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez:
Statistical Hypothesis Testing for Class-Conditional Label Noise. CoRR abs/2103.02630 (2021) - [i8]Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki:
On the overlooked issue of defining explanation objectives for local-surrogate explainers. CoRR abs/2106.05810 (2021) - [i7]Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki:
Understanding surrogate explanations: the interplay between complexity, fidelity and coverage. CoRR abs/2107.04309 (2021) - [i6]Rafael Poyiadzi, Jie Shen, Stavros Petridis, Yujiang Wang, Maja Pantic:
Domain Generalisation for Apparent Emotional Facial Expression Recognition across Age-Groups. CoRR abs/2110.09168 (2021) - [i5]Jonas Schulz, Rafael Poyiadzi, Raúl Santos-Rodríguez:
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach. CoRR abs/2111.09121 (2021) - 2020
- [j1]Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach:
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. J. Open Source Softw. 5(49): 1904 (2020) - [c5]Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodríguez, Tijl De Bie, Peter A. Flach:
FACE: Feasible and Actionable Counterfactual Explanations. AIES 2020: 344-350 - [c4]Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey:
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. AAI4H@ECAI 2020: 23-27 - [d1]Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach:
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. Zenodo, 2020
- [i4]Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey:
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. CoRR abs/2007.03615 (2020)
2010 – 2019
- 2019
- [c3]Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey:
Active Learning with Label Proportions. ICASSP 2019: 3097-3101 - [i3]Niall Twomey, Rafael Poyiadzi, Callum Mann, Raúl Santos-Rodríguez:
Ordinal Regression as Structured Classification. CoRR abs/1905.13658 (2019) - [i2]Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodriguez, Tijl De Bie, Peter A. Flach:
FACE: Feasible and Actionable Counterfactual Explanations. CoRR abs/1909.09369 (2019) - 2018
- [c2]Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey:
Label Propagation for Learning with Label proportions. MLSP 2018: 1-6 - [c1]Rafael Poyiadzi, Raúl Santos-Rodríguez, Tijl De Bie:
Ordinal Label Proportions. ECML/PKDD (1) 2018: 306-321 - [i1]Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey:
Label Propagation for Learning with Label Proportions. CoRR abs/1810.10328 (2018)
Coauthor Index
aka: Raúl Santos-Rodriguez
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last updated on 2024-10-21 21:29 CEST by the dblp team
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