Browse by UCL people
Group by: Type | Date
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Number of items: 50.
Article
Andersson, TR;
Hosking, JS;
Pérez-Ortiz, M;
Paige, B;
Elliott, A;
Russell, C;
Law, S;
... Shuckburgh, E; + view all
(2021)
Seasonal Arctic sea ice forecasting with probabilistic deep learning.
Nature Communications
, 12
(1)
, Article 5124. 10.1038/s41467-021-25257-4.
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Anggunia, Sofiarti Dyah;
Sowell, Jesse;
Pérez-Ortiz, María;
(2025)
Decoding development: the AI frontier in policy crafting: A systematic review.
Data & Policy
, 7
, Article e31. 10.1017/dap.2025.10.
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Bulathwela, Sahan;
Perez-Ortiz, Maria;
Yilmaz, Emine;
Shawe-Taylor, John;
(2022)
Power to the Learner: Towards Human-Intuitive and Integrative Recommendations with Open Educational Resources.
Sustainability
, 14
(18)
, Article 11682. 10.3390/su141811682.
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Dolores Ayllón, M;
Ciria, R;
Cruz-Ramirez, M;
Perez-Ortiz, M;
Gómez, I;
Valente, R;
O'Grady, J;
... Briceño, J; + view all
(2018)
Validation of artificial neural networks as a methodology for donor‐recipient matching for liver transplantation.
Liver Transplantation
, 24
(2)
pp. 192-203.
10.1002/lt.24870.
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Dorado-Moreno, M;
Perez-Ortiz, M;
Gutierrez, PA;
Ciria, R;
Briceno, J;
Hervas-Martinez, C;
(2017)
Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem.
Artificial Intelligence in Medicine
, 77
pp. 1-11.
10.1016/j.artmed.2017.02.004.
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Mesías-Ruiz, Gustavo A;
Pérez-Ortiz, María;
Dorado, José;
de Castro, Ana I;
Peña, José M;
(2023)
Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review.
Frontiers in Plant Science
, 14
, Article 1143326. 10.3389/fpls.2023.1143326.
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Mikhailiuk, A;
Perez-Ortiz, M;
Yue, D;
Suen, WS;
Mantiuk, R;
(2021)
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality.
IEEE Transactions on Multimedia
10.1109/TMM.2021.3076298.
(In press).
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Pérez-Ortiz, M;
Rivasplata, O;
Shawe-Taylor, J;
Szepesvári, C;
(2021)
Tighter risk certificates for neural networks.
Journal of Machine Learning Research
, 22
, Article 227.
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Pérez-Ortiz, M;
Durán-Rosal, AM;
Gutiérrez, PA;
Sánchez-Monedero, J;
Nikolaou, A;
Fernández-Navarro, F;
Hervás-Martínez, C;
(2017)
On the use of evolutionary time series analysis for segmenting paleoclimate data.
Neurocomputing
10.1016/j.neucom.2016.11.101.
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Perez-Ortiz, M;
Gutierrez, PA;
Ayllon-Teran, MD;
Heaton, N;
Ciria, R;
Briceno, J;
Hervas-Martinez, C;
(2017)
Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation.
Knowledge-Based Systems
, 123
pp. 75-87.
10.1016/j.knosys.2017.02.020.
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Perez-Ortiz, M;
Gutierrez, PA;
Carbonero-Ruz, M;
Hervas-Martinez, C;
(2016)
Semi-supervised learning for ordinal Kernel Discriminant Analysis.
Neural Networks
, 84
pp. 57-66.
10.1016/j.neunet.2016.08.004.
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Perez-Ortiz, M;
Jimenez-Fernandez, S;
Gutierrez, PA;
Alexandre, E;
Hervas-Martinez, C;
Salcedo-Sanz, S;
(2016)
A Review of Classification Problems and Algorithms in Renewable Energy Applications.
[Review].
Energies
, 9
(8)
, Article 607. 10.3390/en9080607.
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Perez-Ortiz, M;
Manuel Pena, J;
Antonio Gutierrez, P;
Torres-Sanchez, J;
Hervas-Martinez, C;
Lopez-Granados, F;
(2016)
Selecting patterns and features for between- and within-crop-row weed mapping using UAV-imagery.
Expert Systems with Applications
, 47
pp. 85-94.
10.1016/j.eswa.2015.10.043.
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Pérez-Ortiz, M;
Mikhailiuk, A;
Zerman, E;
Hulusic, V;
Valenzise, G;
Mantiuk, RK;
(2020)
From Pairwise Comparisons and Rating to a Unified Quality Scale.
IEEE Transactions on Image Processing
, 29
pp. 1139-1151.
10.1109/TIP.2019.2936103.
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Sánchez-Monedero, J;
Gutiérrez, PA;
Perez-Ortiz, M;
(2019)
ORCA: A Matlab/Octave Toolbox for Ordinal Regression.
Journal of Machine Learning Research
, 20
, Article 125.
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Sanchez-Monedero, J;
Perez-Ortiz, M;
Saez, A;
Antonio Gutierrez, P;
Hervas-Martinez, C;
(2018)
Partial order label decomposition approaches for melanoma diagnosis.
Applied Soft Computing
, 64
pp. 341-355.
10.1016/j.asoc.2017.11.042.
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Wuerger, S;
Ashraf, M;
Kim, M;
Martinovic, J;
Pérez-Ortiz, M;
Mantiuk, RK;
(2020)
Spatio-chromatic contrast sensitivity under mesopic and photopic light levels.
Journal of Vision
, 20
(4)
, Article 23. 10.1167/jov.20.4.23.
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Book chapter
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Bulathwela, S;
Pérez-Ortiz, M;
Yilmaz, E;
Shawe-Taylor, J;
(2023)
Leveraging Semantic Knowledge Graphs in Educational Recommenders to Address the Cold-Start Problem.
In:
Semantic AI in Knowledge Graphs.
(pp. 1-20).
CRC Press
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Proceedings paper
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Antonio Gutierrez, P;
Perez-Ortiz, M;
Suarez, A;
(2018)
Class Switching Ensembles for Ordinal Regression.
In: Rojas, I and Joya, G and Catala, A, (eds.)
Advances in Computational Intelligence (Proceedings Part 1).
(pp. pp. 408-419).
Springer: Cham, Switzerland.
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Bulathwela, S;
Pérez-Ortiz, M;
Holloway, C;
Shawe-Taylor, J;
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution.
In:
NeurIPS 2021 Workshop on Machine Learning for the Developing World (ML4D).
NeurIPS
(In press).
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Bulathwela, S;
Pérez-Ortiz, M;
Yilmaz, E;
Shawe-Taylor, J;
(2022)
Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems.
In:
Proceedings of First International Workshop on Joint Use of Probabilistic Graphical Models and Ontology at Conference on Knowledge Graph and Semantic Web 2021.
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Bulathwela, Sahan;
Perez-Ortiz, Maria;
Novak, Erik;
Yilmaz, Emine;
Shawe-Taylor, John;
(2021)
PEEK: A Large Dataset of Learner Engagement with Educational Videos.
In:
Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling (ORSUM 2021), in conjunction with the 15th ACM Conference on Recommender Systems.
ORSUM: Amsterdam, The Netherlands.
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Bulathwela, Sahan;
Verma, Meghana;
Perez-Ortiz, Maria;
Yilmaz, Emine;
Shawe-Taylor, John;
(2022)
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments.
In:
Proceedings of the 15th International Conference on Educational Data Mining, July 2022.
(pp. pp. 414-421).
International Educational Data Mining Society
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Bulathwela, S;
Kreitmayer, S;
Pérez-Ortiz, M;
(2020)
What's in it for me?: Augmenting recommended learning resources with navigable annotations.
In:
IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces Companion.
(pp. pp. 114-115).
Association for Computing Machinery: New York, NY, USA.
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Bulathwela, S;
PAerez-Ortiz, M;
Yilmaz, E;
Shawe-Taylor, J;
(2020)
Towards an Integrative Educational Recommender for Lifelong Learners.
In:
Proceedings of the AAAI Conference on Artificial Intelligence.
(pp. pp. 13759-13760).
Association for the Advancement of Artificial Intelligence (AAAI)
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Bulathwela, S;
Pérez-Ortiz, M;
Lipani, A;
Yilmaz, E;
Shawe-Taylor, J;
(2020)
Predicting Engagement in Video Lectures.
In:
Proceedings of The 13th International Conference on Educational Data Mining (EDM 2020).
(pp. pp. 50-60).
Educational Data Mining (EDM)
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Bulathwela, S;
Pérez-Ortiz, M;
Mehrotra, R;
Orlic, D;
De La Higuera, C;
Shawe-Taylor, J;
Yilmaz, E;
(2020)
SUM’20: State-based user modelling.
In:
WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining.
(pp. pp. 899-900).
ACM: Houston, TX, USA.
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Bulathwela, S;
Pérez-Ortiz, M;
Yilmaz, E;
Shawe-Taylor, J;
(2020)
TrueLearn: A family of bayesian algorithms to match lifelong learners to open educational resources.
In:
AAAI Technical Track: Applications.
(pp. pp. 565-573).
AAAI
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Dixon, Ben;
Bieker, Jacob;
Perez Ortiz, Maria;
(2022)
Comparing the carbon costs and benefits of low-resource solar nowcasting.
In:
NeurIPS 2022 Workshop on Tackling Climate Change with Machine Learning.
(pp. p. 58).
NeurIPS: virtual.
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Javier Maestre-Garcia, F;
Garcia-Martinez, C;
Perez-Ortiz, M;
Antonio Gutierrez, P;
(2017)
An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning.
In: Rojas, I and Joya, G and Catala, A, (eds.)
Advances in Computational Intelligence (Proceedings Part 2).
(pp. pp. 513-524).
Springer: Cham, Switzerland.
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Mikhailiuk, A;
Perez-Ortiz, M;
Mantiuk, R;
(2018)
Psychometric scaling of TID2013 dataset.
In: Atzori, L, (ed.)
Proceedings of the 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX).
IEEE: Cagliari, Italy.
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Mikhailiuk, A;
Wilmot, C;
Perez-Ortiz, M;
Yue, D;
Mantiuk, R;
(2020)
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization.
In:
Proceedings - International Conference on Pattern Recognition.
IEEE: Milan, Italy.
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Perez-Ortiz, M;
Rivasplata, O;
Parrado-Hernandez, E;
Guedj, B;
Shawe-Taylor, J;
(2021)
Progress in Self-Certified Neural Networks.
In:
Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021).
NeurIPS
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Perez-Ortiz, Maria;
Bulathwela, Sahan;
Dormann, Claire;
Verma, Meghana;
Kreitmayer, Stefan;
Noss, Richard;
Shawe-Taylor, John;
... Yilmaz, Emine; + view all
(2022)
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
In:
CHIIR '22: Proceedings of the 2022 Conference on Human Information Interaction and Retrieval.
(pp. pp. 90-101).
ACM
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Perez-Ortiz, M;
Dormann, C;
Rogers, Y;
Bulathwela, S;
Kreitmayer, S;
Yilmaz, E;
Noss, R;
(2021)
X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI.
In:
Proceedings of the 26th International Conference on Intelligent User Interfaces.
(pp. pp. 70-74).
ACM: Association for Computing Machinery: New York, NY, USA.
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Perez-Ortiz, M;
Fernandes, K;
Cruz, R;
Cardoso, JS;
Briceno, J;
Hervas-Martinez, C;
(2017)
Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation.
In: Rojas, I and Joya, G and Catala, A, (eds.)
Advances in Computational Intelligence (Proceedings Part 1).
(pp. pp. 525-537).
Springer: Cham, Switzerland.
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Pérez-Ortiz, M;
Gutiérrez, PA;
Tino, P;
Casanova-Mateo, C;
Salcedo-Sanz, S;
(2018)
A mixture of experts model for predicting persistent weather patterns.
In: Marley, Vallasco and Pablo, Estevez, (eds.)
Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN 2018).
IEEE: Piscataway, NJ, USA.
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Perez-Ortiz, M;
Tino, P;
Mantiuk, R;
Hervas-Martinez, C;
(2019)
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets.
In:
Proceedings of Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19).
(pp. pp. 4715-4722).
AAAI Press: Honolulu, Hawaii, USA.
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Qiu, Y;
Djemili, K;
Elezi, D;
Srazali, AS;
Pérez-Ortiz, M;
Yilmaz, E;
Shawe-Taylor, J;
(2024)
A Toolbox for Modelling Engagement with Educational Videos.
In:
Proceedings of the AAAI Conference on Artificial Intelligence.
(pp. pp. 23128-23136).
Association for the Advancement of Artificial Intelligence (AAAI)
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Rudd-Jones, J;
Musolesi, M;
Pérez-Ortiz, M;
(2025)
Multi-Agent Reinforcement Learning Simulation for Environmental Policy Synthesis.
In:
AAMAS '25: Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems.
(pp. pp. 2890-2895).
ACM (Association for Computing Machinery): Detroit, MI, USA.
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Ye, N;
Perez-Ortiz, M;
Mantiuk, RK;
(2020)
Visibility Metric for Visually Lossless Image Compression.
In:
Proceedings of the 2019 Picture Coding Symposium (PCS).
IEEE
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Ye, N;
Perez-Ortiz, M;
Mantiuk, RK;
(2018)
Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video.
In: Nikou, Christophoros and Plataniotis, Kostas, (eds.)
Proceedings of the 25th IEEE International Conference on Image Processing (ICIP 2018).
(pp. pp. 1718-1722).
IEEE: Athens, Greece.
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Report
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Perez-Ortiz, Maria;
Novak, Erik;
Bulathwela, Sahan;
Shawe-Taylor, John;
(2020)
An AI-based Learning Companion Promoting Lifelong Learning Opportunities for All.
(Opinion Series Report
).
UNESCO; International Research Centre in Artificial Intelligence (IRCAI)
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Working / discussion paper
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Bulathwela, Sahan;
Perez-Ortiz, Maria;
Yilmaz, Emine;
Shawe-Taylor, John;
(2020)
VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement.
ArXiv
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Cantelobre, Théophile;
Guedj, Benjamin;
Pérez-Ortiz, María;
Shawe-Taylor, John;
(2020)
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings.
ArXiv
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Dixon, Ben;
Pérez-Ortiz, María;
Bieker, Jacob;
(2022)
Comparing the carbon costs and benefits of low-resource solar nowcasting.
arXiv: Ithaca, NY, USA.
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Lee, F;
Perez Ortiz, M;
Shawe-Taylor, J;
(2021)
Computational modelling of COVID-19: A study of compliance and superspreaders.
MedRxiv: Cold Spring Harbor, NY, USA.
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Perez-Ortiz, Maria;
Mantiuk, Rafal K;
(2017)
A practical guide and software for analysing pairwise comparison experiments.
arXiv: Ithaca, NY, USA.
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Perez-Ortiz, Maria;
Rivasplata, Omar;
Guedj, Benjamin;
Gleeson, Matthew;
Zhang, Jingyu;
Shawe-Taylor, John;
Bober, Miroslaw;
(2021)
Learning PAC-Bayes Priors for Probabilistic Neural Networks.
ArXiv: Ithaca, NY, USA.
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Conference item
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Perez-Ortiz, M;
Martinovic, J;
Mantiuk, R;
Wuerger, S;
(2019)
Luminance and Chromatic Contrast Sensitivity at High Light Levels.
Presented at: 41st European Conference on Visual Perception (ECVP), Trieste, Italy.
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