María Pérez-Ortiz

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 70

Top Topics

Pairwise Comparison

Ordinal Regression

Top Venues

Publications

Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman Srazali, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor, Sahan Bulathwela
A Toolbox for Modelling Engagement with Educational Videos. AAAI (2024)
Nicolas Belissent, José M. Peña, Gustavo A. Mesías-Ruiz, John Shawe-Taylor, María Pérez-Ortiz
Transfer and zero-shot learning for scalable weed detection and classification in UAV images. Knowl. Based Syst. 292 (2024)
Xiao Fu, María Pérez-Ortiz, Aldo Lipani
An Analysis of Stopping Strategies in Conversational Search Systems. ICTIR (2024)
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 (2024)
Henning Heyen, Amy Widdicombe, Noah Y. Siegel, María Pérez-Ortiz, Philip Treleaven
The Effect of Model Size on LLM Post-hoc Explainability via LIME. CoRR (2024)
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 (2024)
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 (2024)
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 (2024)
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 (2024)
Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman, María Pérez-Ortiz, Sahan Bulathwela
TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback. CoRR (2023)
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)
Theodore Wolf, Nantas Nardelli, John Shawe-Taylor, María Pérez-Ortiz
Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models. CoRR (2023)
Sahan Bulathwela, Meghana Verma, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments. CoRR (2022)
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 (2022)
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? CHIIR (2022)
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)
Ben Dixon, María Pérez-Ortiz, Jacob Bieker
Comparing the carbon costs and benefits of low-resource solar nowcasting. CoRR (2022)
Aliaksei Mikhailiuk, María Pérez-Ortiz, Dingcheng Yue, Wilson Suen, Rafal K. Mantiuk
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality. IEEE Trans. Multim. 24 (2022)
Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems. CoRR (2021)
María Pérez-Ortiz, Omar Risvaplata, John Shawe-Taylor, Csaba Szepesvári
Tighter Risk Certificates for Neural Networks. J. Mach. Learn. Res. 22 (2021)
Sahan Bulathwela, María Pérez-Ortiz, Catherine Holloway, John Shawe-Taylor
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution. CoRR (2021)
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 (2021)
Sahan Bulathwela, María Pérez-Ortiz, Erik Novak, Emine Yilmaz, John Shawe-Taylor
PEEK: A Large Dataset of Learner Engagement with Educational Videos. CoRR (2021)
María Pérez-Ortiz, Claire Dormann, Yvonne Rogers, Sahan Bulathwela, Stefan Kreitmayer, Emine Yilmaz, Richard Noss, John Shawe-Taylor
X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI. IUI Companion (2021)
María Pérez-Ortiz, Erik Novak, Sahan Bulathwela, John Shawe-Taylor
An AI-based Learning Companion Promoting Lifelong Learning Opportunities for All. CoRR (2021)
María Pérez-Ortiz, Omar Rivasplata, Emilio Parrado-Hernández, Benjamin Guedj, John Shawe-Taylor
Progress in Self-Certified Neural Networks. CoRR (2021)
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 (2020)
María Pérez-Ortiz, Aliaksei Mikhailiuk, Emin Zerman, Vedad Hulusic, Giuseppe Valenzise, Rafal K. Mantiuk
From Pairwise Comparisons and Rating to a Unified Quality Scale. IEEE Trans. Image Process. 29 (2020)
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)
Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor
Predicting Engagement in Video Lectures. CoRR (2020)
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)
Sahan Bulathwela, Stefan Kreitmayer, María Pérez-Ortiz
What's in it for me?: Augmenting Recommended Learning Resources with Navigable Annotations. IUI Companion (2020)
Aliaksei Mikhailiuk, María Pérez-Ortiz, Dingcheng Yue, Wilson Suen, Rafal K. Mantiuk
Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality. CoRR (2020)
Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
Towards an Integrative Educational Recommender for Lifelong Learners (Student Abstract). AAAI (2020)
Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement. CoRR (2020)
Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz, John Shawe-Taylor
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings. CoRR (2020)
María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári
Tighter risk certificates for neural networks. CoRR (2020)
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) (2020)
Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor
Predicting Engagement in Video Lectures. EDM (2020)
Sahan Bulathwela, María Pérez-Ortiz, Rishabh Mehrotra, Davor Orlic, Colin de la Higuera, John Shawe-Taylor, Emine Yilmaz
SUM'20: State-based User Modelling. WSDM (2020)
Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor
Towards an Integrative Educational Recommender for Lifelong Learners. CoRR (2019)
Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk
Visibility Metric for Visually Lossless Image Compression. PCS (2019)
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 (2019)
María Pérez-Ortiz, Antonio Manuel Durán-Rosal, Pedro Antonio Gutiérrez, Javier Sánchez-Monedero, Athanasia Nikolaou, Francisco Fernández-Navarro, César Hervás-Martínez
On the use of evolutionary time series analysis for segmenting paleoclimate data. Neurocomputing (2019)
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 (2019)
María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. CoRR (2019)
Javier Sánchez-Monedero, Pedro Antonio Gutiérrez, María Pérez-Ortiz
ORCA: A Matlab/Octave Toolbox for Ordinal Regression. J. Mach. Learn. Res. 20 (2019)
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)
Ricardo Cruz, Kelwin Fernandes, Joaquim F. Pinto da Costa, María Pérez-Ortiz, Jaime S. Cardoso
Binary ranking for ordinal class imbalance. Pattern Anal. Appl. 21 (4) (2018)
Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk
Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video. ICIP (2018)
Aliaksei Mikhailiuk, María Pérez-Ortiz, Rafal Mantiuk
Psychometric scaling of TID2013 dataset. QoMEX (2018)
Javier Sánchez-Monedero, María Pérez-Ortiz, Aurora Sáez, Pedro Antonio Gutiérrez, César Hervás-Martínez
Partial order label decomposition approaches for melanoma diagnosis. Appl. Soft Comput. 64 (2018)
Ricardo Cruz, Kelwin Fernandes, Joaquim F. Pinto da Costa, María Pérez-Ortiz, Jaime S. Cardoso
Combining Ranking with Traditional Methods for Ordinal Class Imbalance. IWANN (2) (2017)
María Pérez-Ortiz, Rafal K. Mantiuk
A practical guide and software for analysing pairwise comparison experiments. CoRR (2017)
María Pérez-Ortiz, Kelwin Fernandes, Ricardo Cruz, Jaime S. Cardoso, Javier Briceño, César Hervás-Martínez
Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation. IWANN (2) (2017)
Ricardo Cruz, Kelwin Fernandes, Joaquim F. Pinto da Costa, María Pérez-Ortiz, Jaime S. Cardoso
Ordinal Class Imbalance with Ranking. IbPRIA (2017)
Pedro Antonio Gutiérrez, María Pérez-Ortiz, Alberto Suárez
Class Switching Ensembles for Ordinal Regression. IWANN (1) (2017)
Manuel Dorado-Moreno, María Pérez-Ortiz, Pedro Antonio Gutiérrez, Rubén Ciria, Javier Briceño, César Hervás-Martínez
Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem. Artif. Intell. Medicine 77 (2017)
Francisco Javier Maestre-García, Carlos García-Martínez, María Pérez-Ortiz, Pedro Antonio Gutiérrez
An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning. IWANN (2) (2017)
María Pérez-Ortiz, Aurora Sáez, Javier Sánchez-Monedero, Pedro Antonio Gutiérrez, César Hervás-Martínez
Tackling the ordinal and imbalance nature of a melanoma image classification problem. IJCNN (2016)
Manuel Dorado-Moreno, María Pérez-Ortiz, María Dolores Ayllón-Terán, Pedro Antonio Gutiérrez, César Hervás-Martínez
Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem. HAIS (2016)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Peter Tiño, César Hervás-Martínez
Oversampling the Minority Class in the Feature Space. IEEE Trans. Neural Networks Learn. Syst. 27 (9) (2016)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz, César Hervás-Martínez
Learning from Label Proportions via an Iterative Weighting Scheme and Discriminant Analysis. CAEPIA (2016)
Pedro Antonio Gutiérrez, María Pérez-Ortiz, Javier Sánchez-Monedero, Francisco Fernández-Navarro, César Hervás-Martínez
Ordinal Regression Methods: Survey and Experimental Study. IEEE Trans. Knowl. Data Eng. 28 (1) (2016)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz, César Hervás-Martínez
Adapting linear discriminant analysis to the paradigm of learning from label proportions. SSCI (2016)
Pedro Antonio Gutiérrez, María Pérez-Ortiz, Javier Sánchez-Monedero, César Hervás-Martínez
Representing ordinal input variables in the context of ordinal classification. IJCNN (2016)
María Pérez-Ortiz, José Manuel Peñá-Barragán, Pedro Antonio Gutiérrez, Jorge Torres-Sánchez, César Hervás-Martínez, Francisca López-Granados
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery. Expert Syst. Appl. 47 (2016)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, José M. Peña, Jorge Torres-Sánchez, Francisca López-Granados, César Hervás-Martínez
Machine learning paradigms for weed mapping via unmanned aerial vehicles. SSCI (2016)
María Pérez-Ortiz, Mercedes Torres-Jiménez, Pedro Antonio Gutiérrez, Javier Sánchez-Monedero, César Hervás-Martínez
Fisher Score-Based Feature Selection for Ordinal Classification: A Social Survey on Subjective Well-Being. HAIS (2016)
Javier Sánchez-Monedero, Aurora Sáez, María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Classification of Melanoma Presence and Thickness Based on Computational Image Analysis. HAIS (2016)
Pedro Antonio Gutiérrez, Juan Carlos Fernández, María Pérez-Ortiz, Laura Cornejo-Bueno, Enrique Alexandre-Cortizo, Sancho Salcedo-Sanz, César Hervás-Martínez
Energy Flux Range Classification by Using a Dynamic Window Autoregressive Model. IWANN (2) (2015)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, José Manuel Peñá-Barragán, Jorge Torres-Sánchez, César Hervás-Martínez, Francisca López-Granados
An Experimental Comparison for the Identification of Weeds in Sunflower Crops via Unmanned Aerial Vehicles and Object-Based Analysis. IWANN (1) (2015)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Manuel Cruz-Ramírez, Javier Sánchez-Monedero, César Hervás-Martínez
Kernelising the Proportional Odds Model through kernel learning techniques. Neurocomputing 164 (2015)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez, Xin Yao
Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression. IEEE Trans. Knowl. Data Eng. 27 (5) (2015)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Incorporating Privileged Information to Improve Manifold Ordinal Regression. IJCCI (NCTA) (2014)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Projection-Based Ensemble Learning for Ordinal Regression. IEEE Trans. Cybern. 44 (5) (2014)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Learning Kernel Label Decompositions for Ordinal Classification Problems. IJCCI (NCTA) (2014)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Manuel Cruz-Ramírez, Javier Sánchez-Monedero, César Hervás-Martínez
Kernelizing the Proportional Odds Model through the Empirical Kernel Mapping. IWANN (1) (2013)
María Pérez-Ortiz, Rosa Colmenarejo, Juan Carlos Fernández Caballero, César Hervás-Martínez
Can Machine Learning Techniques Help to Improve the Common Fisheries Policy? IWANN (2) (2013)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Synthetic over-sampling in the empirical feature space. ESANN (2013)
Javier Sánchez-Monedero, Pedro Antonio Gutiérrez, María Pérez-Ortiz, César Hervás-Martínez
An n-Spheres Based Synthetic Data Generator for Supervised Classification. IWANN (1) (2013)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, César Hervás-Martínez
Borderline Kernel Based Over-Sampling. HAIS (2013)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Javier Sánchez-Monedero, César Hervás-Martínez
Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment. ESANN (2013)
Manuel Cruz-Ramírez, César Hervás-Martínez, Pedro Antonio Gutiérrez, María Pérez-Ortiz, Javier Briceño, Manuel de la Mata
Memetic Pareto differential evolutionary neural network used to solve an unbalanced liver transplantation problem. Soft Comput. 17 (2) (2013)