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María Pérez-Ortiz 0001
M. Pérez-Ortiz 0001
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- affiliation: University College London, AI Centre, United Kingdom
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2020 – today
- 2024
- [j25]Nicolas Belissent, José M. Peña
, Gustavo A. Mesías-Ruiz, John Shawe-Taylor
Transfer and zero-shot learning for scalable weed detection and classification in UAV images. Knowl. Based Syst. 292: 111586 (2024) - [c50]Yuxiang Qiu
A Toolbox for Modelling Engagement with Educational Videos. AAAI 2024: 23128-23136 - [c49]Noah Y. Siegel, Oana-Maria Camburu, Nicolas Heess, María Pérez-Ortiz:
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models. ACL (Short Papers) 2024: 530-546 - [c48]Xiao Fu
An Analysis of Stopping Strategies in Conversational Search Systems. ICTIR 2024: 247-257 - [i28]Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor, Sahan Bulathwela:
A Toolbox for Modelling Engagement with Educational Videos. CoRR abs/2401.05424 (2024) - [i27]Zekun Wu, Sahan Bulathwela, María Pérez-Ortiz, Adriano Soares Koshiyama:
Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation. CoRR abs/2404.01768 (2024) - [i26]Noah Y. Siegel, Oana-Maria Camburu, Nicolas Heess, María Pérez-Ortiz:
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models. CoRR abs/2404.03189 (2024) - [i25]Henning Heyen, Amy Widdicombe, Noah Y. Siegel, María Pérez-Ortiz, Philip C. Treleaven:
The Effect of Model Size on LLM Post-hoc Explainability via LIME. CoRR abs/2405.05348 (2024) - [i24]Ze Wang, Zekun Wu, Xin Guan, Michael Thaler, Adriano S. Koshiyama, Skylar Lu, Sachin Beepath, Ediz Ertekin Jr., María Pérez-Ortiz:
JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models. CoRR abs/2406.15484 (2024) - [i23]Nathan Herr, Fernando Acero, Roberta Raileanu, María Pérez-Ortiz, Zhibin Li:
Are Large Language Models Strategic Decision Makers? A Study of Performance and Bias in Two-Player Non-Zero-Sum Games. CoRR abs/2407.04467 (2024) - 2023
- [c47]Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman, María Pérez-Ortiz, Sahan Bulathwela:
TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback. ORSUM@RecSys 2023 - [i22]Yuxiang Qiu
TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback. CoRR abs/2309.11527 (2023) - [i21]Theodore Wolf, Nantas Nardelli, John Shawe-Taylor, María Pérez-Ortiz:
Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models. CoRR abs/2312.06527 (2023) - 2022
- [j24]Aliaksei Mikhailiuk
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality. IEEE Trans. Multim. 24: 2125-2138 (2022) - [c46]María Pérez-Ortiz, Sahan Bulathwela
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos? CHIIR 2022: 90-101 - [c45]Sahan Bulathwela, Meghana Verma, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor:
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments. EDM 2022 - [e1]Stefan Schlobach, María Pérez-Ortiz, Myrthe Tielman:
HHAI 2022: Augmenting Human Intellect - Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence, Amsterdam, The Netherlands, 13-17 June 2022. Frontiers in Artificial Intelligence and Applications 354, IOS Press 2022, ISBN 978-1-64368-308-9 [contents] - [i20]María Pérez-Ortiz, Sahan Bulathwela, Claire Dormann, Meghana Verma, Stefan Kreitmayer, Richard Noss, John Shawe-Taylor, Yvonne Rogers, Emine Yilmaz:
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos? CoRR abs/2201.03408 (2022) - [i19]Sahan Bulathwela
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments. CoRR abs/2207.01504 (2022) - [i18]Ben Dixon, María Pérez-Ortiz, Jacob Bieker:
Comparing the carbon costs and benefits of low-resource solar nowcasting. CoRR abs/2210.04554 (2022) - 2021
- [j23]María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári:
Tighter Risk Certificates for Neural Networks. J. Mach. Learn. Res. 22: 227:1-227:40 (2021) - [c44]María Pérez-Ortiz, Claire Dormann, Yvonne Rogers, Sahan Bulathwela
X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI. IUI Companion 2021: 70-74 - [i17]Sahan Bulathwela, María Pérez-Ortiz, Erik Novak, Emine Yilmaz, John Shawe-Taylor:
PEEK: A Large Dataset of Learner Engagement with Educational Videos. CoRR abs/2109.03154 (2021) - [i16]María Pérez-Ortiz, Omar Rivasplata, Benjamin Guedj, Matthew Gleeson, Jingyu Zhang, John Shawe-Taylor, Miroslaw Bober, Josef Kittler:
Learning PAC-Bayes Priors for Probabilistic Neural Networks. CoRR abs/2109.10304 (2021) - [i15]María Pérez-Ortiz, Omar Rivasplata, Emilio Parrado-Hernández, Benjamin Guedj, John Shawe-Taylor:
Progress in Self-Certified Neural Networks. CoRR abs/2111.07737 (2021) - [i14]María Pérez-Ortiz, Erik Novak, Sahan Bulathwela, John Shawe-Taylor:
An AI-based Learning Companion Promoting Lifelong Learning Opportunities for All. CoRR abs/2112.01242 (2021) - [i13]Sahan Bulathwela, María Pérez-Ortiz, Catherine Holloway, John Shawe-Taylor:
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution. CoRR abs/2112.02034 (2021) - [i12]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor:
Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems. CoRR abs/2112.04368 (2021) - 2020
- [j22]Sahan Bulathwela, María Pérez-Ortiz, Rishabh Mehrotra, Davor Orlic, Colin de la Higuera, John Shawe-Taylor, Emine Yilmaz:
Report on the WSDM 2020 workshop on state-based user modelling (SUM'20). SIGIR Forum 54(1): 5:1-5:11 (2020) - [j21]María Pérez-Ortiz
From Pairwise Comparisons and Rating to a Unified Quality Scale. IEEE Trans. Image Process. 29: 1139-1151 (2020) - [c43]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources. AAAI 2020: 565-573 - [c42]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
Towards an Integrative Educational Recommender for Lifelong Learners (Student Abstract). AAAI 2020: 13759-13760 - [c41]Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor:
Predicting Engagement in Video Lectures. EDM 2020 - [c40]Aliaksei Mikhailiuk, Clifford Wilmot, María Pérez-Ortiz, Dingcheng Yue, Rafal K. Mantiuk:
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization. ICPR 2020: 2559-2566 - [c39]Sahan Bulathwela
What's in it for me?: Augmenting Recommended Learning Resources with Navigable Annotations. IUI Companion 2020: 114-115 - [c38]Sahan Bulathwela
SUM'20: State-based User Modelling. WSDM 2020: 899-900 - [i11]Aliaksei Mikhailiuk, Clifford Wilmot, María Pérez-Ortiz, Dingcheng Yue, Rafal Mantiuk:
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization. CoRR abs/2004.05691 (2020) - [i10]Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor:
Predicting Engagement in Video Lectures. CoRR abs/2006.00592 (2020) - [i9]María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári:
Tighter risk certificates for neural networks. CoRR abs/2007.12911 (2020) - [i8]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor:
VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement. CoRR abs/2011.02273 (2020) - [i7]Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz, John Shawe-Taylor:
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings. CoRR abs/2012.03780 (2020) - [i6]Aliaksei Mikhailiuk, María Pérez-Ortiz, Dingcheng Yue, Wilson Suen, Rafal K. Mantiuk:
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality. CoRR abs/2012.10758 (2020)
2010 – 2019
- 2019
- [j20]María Pérez-Ortiz
On the use of evolutionary time series analysis for segmenting paleoclimate data. Neurocomputing 326-327: 3-14 (2019) - [j19]Javier Sánchez-Monedero, Pedro Antonio Gutiérrez, María Pérez-Ortiz:
ORCA: A Matlab/Octave Toolbox for Ordinal Regression. J. Mach. Learn. Res. 20: 125:1-125:5 (2019) - [c37]María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez:
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. AAAI 2019: 4715-4722 - [c36]Nanyang Ye, María Pérez-Ortiz
Visibility Metric for Visually Lossless Image Compression. PCS 2019: 1-5 - [i5]María Pérez-Ortiz, Pedro Antonio Gutiérrez, Peter Tiño, Carlos Casanova-Mateo, Sancho Salcedo-Sanz:
A mixture of experts model for predicting persistent weather patterns. CoRR abs/1903.10012 (2019) - [i4]María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez:
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. CoRR abs/1903.10022 (2019) - [i3]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor:
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources. CoRR abs/1911.09471 (2019) - [i2]Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor:
Towards an Integrative Educational Recommender for Lifelong Learners. CoRR abs/1912.01592 (2019) - 2018
- [j18]Javier Sánchez-Monedero
Partial order label decomposition approaches for melanoma diagnosis. Appl. Soft Comput. 64: 341-355 (2018) - [j17]Ricardo P. M. Cruz
Binary ranking for ordinal class imbalance. Pattern Anal. Appl. 21(4): 931-939 (2018) - [c35]Nanyang Ye, María Pérez-Ortiz
Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video. ICIP 2018: 1718-1722 - [c34]M. Pérez-Ortiz
A mixture of experts model for predicting persistent weather patterns. IJCNN 2018: 1-8 - [c33]Aliaksei Mikhailiuk, María Pérez-Ortiz
Psychometric scaling of TID2013 dataset. QoMEX 2018: 1-6 - 2017
- [j16]Manuel Dorado-Moreno
Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem. Artif. Intell. Medicine 77: 1-11 (2017) - [j15]M. Pérez-Ortiz
Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation. Knowl. Based Syst. 123: 75-87 (2017) - [c32]Ricardo P. M. Cruz
Ordinal Class Imbalance with Ranking. IbPRIA 2017: 3-12 - [c31]Pedro Antonio Gutiérrez
Class Switching Ensembles for Ordinal Regression. IWANN (1) 2017: 408-419 - [c30]Francisco Javier Maestre-García, Carlos García-Martínez
An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning. IWANN (2) 2017: 513-524 - [c29]María Pérez-Ortiz
Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation. IWANN (2) 2017: 525-537 - [c28]Ricardo P. M. Cruz
Combining Ranking with Traditional Methods for Ordinal Class Imbalance. IWANN (2) 2017: 538-548 - [i1]María Pérez-Ortiz, Rafal K. Mantiuk:
A practical guide and software for analysing pairwise comparison experiments. CoRR abs/1712.03686 (2017) - 2016
- [j14]María Pérez-Ortiz
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery. Expert Syst. Appl. 47: 85-94 (2016) - [j13]M. Pérez-Ortiz
Semi-supervised learning for ordinal Kernel Discriminant Analysis. Neural Networks 84: 57-66 (2016) - [j12]M. Pérez-Ortiz
A Study on Multi-Scale Kernel Optimisation via Centered Kernel-Target Alignment. Neural Process. Lett. 44(2): 491-517 (2016) - [j11]M. Pérez-Ortiz
On the Use of Nominal and Ordinal Classifiers for the Discrimination of States of Development in Fish Oocytes. Neural Process. Lett. 44(2): 555-570 (2016) - [j10]Pedro Antonio Gutiérrez
Ordinal Regression Methods: Survey and Experimental Study. IEEE Trans. Knowl. Data Eng. 28(1): 127-146 (2016) - [j9]María Pérez-Ortiz
Oversampling the Minority Class in the Feature Space. IEEE Trans. Neural Networks Learn. Syst. 27(9): 1947-1961 (2016) - [c27]María Pérez-Ortiz
Learning from Label Proportions via an Iterative Weighting Scheme and Discriminant Analysis. CAEPIA 2016: 79-88 - [c26]Javier Sánchez-Monedero
Classification of Melanoma Presence and Thickness Based on Computational Image Analysis. HAIS 2016: 427-438 - [c25]Manuel Dorado-Moreno, María Pérez-Ortiz
Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem. HAIS 2016: 451-462 - [c24]María Pérez-Ortiz
Fisher Score-Based Feature Selection for Ordinal Classification: A Social Survey on Subjective Well-Being. HAIS 2016: 597-608 - [c23]María Pérez-Ortiz
Tackling the ordinal and imbalance nature of a melanoma image classification problem. IJCNN 2016: 2156-2163 - [c22]Pedro Antonio Gutiérrez
Representing ordinal input variables in the context of ordinal classification. IJCNN 2016: 2174-2181 - [c21]María Pérez-Ortiz
Machine learning paradigms for weed mapping via unmanned aerial vehicles. SSCI 2016: 1-8 - [c20]María Pérez-Ortiz
Adapting linear discriminant analysis to the paradigm of learning from label proportions. SSCI 2016: 1-7 - 2015
- [j8]M. Pérez-Ortiz
A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method. Appl. Soft Comput. 37: 533-544 (2015) - [j7]María Pérez-Ortiz
Kernelising the Proportional Odds Model through kernel learning techniques. Neurocomputing 164: 23-33 (2015) - [j6]María Pérez-Ortiz
Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression. IEEE Trans. Knowl. Data Eng. 27(5): 1233-1245 (2015) - [c19]Pedro Antonio Gutiérrez
Energy Flux Range Classification by Using a Dynamic Window Autoregressive Model. IWANN (2) 2015: 92-102 - [c18]María Pérez-Ortiz
An Experimental Comparison for the Identification of Weeds in Sunflower Crops via Unmanned Aerial Vehicles and Object-Based Analysis. IWANN (1) 2015: 252-262 - 2014
- [j5]M. Pérez-Ortiz
An organ allocation system for liver transplantation based on ordinal regression. Appl. Soft Comput. 14: 88-98 (2014) - [j4]Laura García-Hernández
An evolutionary neural system for incorporating expert knowledge into the UA-FLP. Neurocomputing 135: 69-78 (2014) - [j3]M. Pérez-Ortiz
Classification of EU countries' progress towards sustainable development based on ordinal regression techniques. Knowl. Based Syst. 66: 178-189 (2014) - [j2]María Pérez-Ortiz, Pedro Antonio Gutiérrez
Projection-Based Ensemble Learning for Ordinal Regression. IEEE Trans. Cybern. 44(5): 681-694 (2014) - [c17]Manuel Cruz-Ramírez
Time Series Segmentation and Statistical Characterisation of the Spanish Stock Market Ibex-35 Index. HAIS 2014: 74-85 - [c16]M. Pérez-Ortiz
Time Series Segmentation of Paleoclimate Tipping Points by an Evolutionary Algorithm. HAIS 2014: 318-329 - [c15]M. Pérez-Ortiz
Log-Gamma Distribution Optimisation via Maximum Likelihood for Ordered Probability Estimates. HAIS 2014: 454-465 - [c14]María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez:
Incorporating Privileged Information to Improve Manifold Ordinal Regression. IJCCI (NCTA) 2014: 187-194 - [c13]María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez:
Learning Kernel Label Decompositions for Ordinal Classification Problems. IJCCI (NCTA) 2014: 218-225 - 2013
- [j1]Manuel Cruz-Ramírez
Memetic Pareto differential evolutionary neural network used to solve an unbalanced liver transplantation problem. Soft Comput. 17(2): 275-284 (2013) - [c12]María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez:
Synthetic over-sampling in the empirical feature space. ESANN 2013 - [c11]María Pérez-Ortiz, Pedro Antonio Gutiérrez, Javier Sánchez-Monedero, César Hervás-Martínez:
Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment. ESANN 2013 - [c10]María Pérez-Ortiz
Borderline Kernel Based Over-Sampling. HAIS 2013: 472-481 - [c9]María Pérez-Ortiz
Kernelizing the Proportional Odds Model through the Empirical Kernel Mapping. IWANN (1) 2013: 270-279 - [c8]María Pérez-Ortiz
Can Machine Learning Techniques Help to Improve the Common Fisheries Policy? IWANN (2) 2013: 278-286 - [c7]Javier Sánchez-Monedero
An n-Spheres Based Synthetic Data Generator for Supervised Classification. IWANN (1) 2013: 613-621 - 2012
- [c6]Pedro Antonio Gutiérrez
An Experimental Study of Different Ordinal Regression Methods and Measures. HAIS (2) 2012: 296-307 - [c5]M. Pérez-Ortiz
Hybrid Multi-objective Machine Learning Classification in Liver Transplantation. HAIS (1) 2012: 397-408 - [c4]M. Pérez-Ortiz
An ensemble approach for ordinal threshold models applied to liver transplantation. IJCNN 2012: 1-8 - [c3]M. Pérez-Ortiz
An Ordinal Regression Approach for the Unequal Area Facility Layout Problem. SOCO 2012: 13-21 - [c2]M. Pérez-Ortiz
A System Learning User Preferences for Multiobjective Optimization of Facility Layouts. SOCO 2012: 43-52 - 2011
- [c1]M. Pérez-Ortiz
Ordinal classification of depression spatial hot-spots of prevalence. ISDA 2011: 1170-1175
Coauthor Index
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last updated on 2024-10-15 00:23 CEST by the dblp team
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