Raúl Santos-Rodríguez

148 papers A* 5A 4B 11C 5Misc 2Journal 91Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HiPP-Prune: Hierarchical Preference-Conditioned Structured Pruning for Vision-Language Models. CoRR Lincen Bai, Hedi Tabia, Raúl Santos-Rodríguez
2026	J	`jnl`	LEMON: Local Explanations via Modality-aware OptimizatioN. CoRR Yu Qin, Phillip Sloan, Raúl Santos-Rodríguez, Majid Mirmehdi, Telmo de Menezes e Silva Filho
2025	J	`jnl`	Active Query Selection for Crowd-Based Reinforcement Learning. CoRR Jonathan Erskine, Taku Yamagata, Raúl Santos-Rodríguez
2025	J	`jnl`	Estimating Information Theoretic Measures via Multidimensional Gaussianization. IEEE Trans. Pattern Anal. Mach. Intell. Valero Laparra, Juan Emmanuel Johnson, Gustau Camps-Valls, Raúl Santos-Rodríguez, Jesús Malo
2025	J	`jnl`	From Research to Certification with Data-Driven Medical Decision Support Systems (Dagstuhl Seminar 25052). Dagstuhl Reports Raúl Santos-Rodríguez, Kacper Sokol, Julia E. Vogt, Sven Wellmann
2025	J	`jnl`	IQM-Vis: A user-centric python toolbox for visualising and evaluating image quality metrics. SoftwareX Matthew Clifford, Alexander Hepburn, Ricardo Kleinlein, Jorge Vila-Tomás, Pablo Hernández-Cámara, Paula Dauden, Nathan F. Lepora, Valero Laparra, Raúl Santos-Rodríguez
2025	J	`jnl`	Improving Local Air Quality Predictions Using Transfer Learning on Satellite Data and Graph Neural Networks. CoRR Finn Gueterbock, Raúl Santos-Rodríguez, Jeffrey N. Clark
2025	J	`jnl`	KnowEEG: Explainable Knowledge Driven EEG Classification. CoRR Amarpal Sahota, Navid Mohammadi Foumani, Raúl Santos-Rodríguez, Zahraa S. Abdallah
2025	J	`jnl`	Machine Learning for Climate Policy: Understanding Policy Progression in the European Green Deal. CoRR Patricia West, Michelle W. L. Wan, Alexander Hepburn, Edwin Simpson, Raúl Santos-Rodríguez, Jeffrey N. Clark
2025	—	`conf`	Optimising Factual Consistency in Summarisation via Preference Learning from Multiple Imperfect Metrics. EMNLP (Findings) Yuxuan Ye, Raúl Santos-Rodríguez, Edwin Simpson
2025	J	`jnl`	Prototype-enhanced prediction in graph neural networks for climate applications. CoRR Nawid Keshtmand, Elena Fillola, Jeffrey Nicholas Clark, Raúl Santos-Rodríguez, Matthew Rigby
2025	J	`jnl`	TACTFL: Temporal Contrastive Training for Multi-modal Federated Learning with Similarity-guided Model Aggregation. CoRR Guanxiong Sun, Majid Mirmehdi, Zahraa S. Abdallah, Raúl Santos-Rodríguez, Ian Craddock, Telmo de Menezes e Silva Filho
2025	J	`jnl`	Uncertainty assessment in satellite-based greenhouse gas emissions estimates using emulated atmospheric transport. CoRR Jeffrey N. Clark, Elena Fillola, Nawid Keshtmand, Raúl Santos-Rodríguez, Matthew Rigby
2024	A*	`conf`	An Interactive Human-Machine Learning Interface for Collecting and Learning from Complex Annotations. IJCAI Jonathan Erskine, Matthew Clifford, Alexander Hepburn, Raúl Santos-Rodríguez
2024	J	`jnl`	An Interactive Human-Machine Learning Interface for Collecting and Learning from Complex Annotations. CoRR Jonathan Erskine, Matthew Clifford, Alexander Hepburn, Raúl Santos-Rodríguez
2024	J	`jnl`	Beyond Pruning Criteria: The Dominant Role of Fine-Tuning and Adaptive Ratios in Neural Network Robustness. CoRR Lincen Bai, Hedi Tabia, Raúl Santos-Rodríguez
2024	J	`jnl`	Evaluation of a Data Annotation Platform for Large, Time-Series Datasets in Intensive Care: Mixed Methods Study. CoRR Marceli Wac, Raúl Santos-Rodríguez, Christopher J. McWilliams, Christopher P. Bourdeaux
2024	J	`jnl`	Explainable AI for Classifying UTI Risk Groups Using a Real-World Linked EHR and Pathology Lab Dataset. CoRR Yujie Dai, Brian Sullivan, Axel Montout, Amy Dillon, Chris Waller, Peter Acs, Rachel Denholm, Philip Williams, Alastair D. Hay, Raúl Santos-Rodríguez, Andrew W. Dowsey
2024	J	`jnl`	Exploring the Requirements of Clinicians for Explainable AI Decision Support Systems in Intensive Care. CoRR Jeffrey N. Clark, Matthew Wragg, Emily Nielsen, Miquel Perelló-Nieto, Nawid Keshtmand, Michael Ambler, Shiv Sharma, Christopher P. Bourdeaux, Amberly Brigden, Raúl Santos-Rodríguez
2024	A*	`conf`	Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. AAAI Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez
2024	—	`conf`	Investigating Brain Connectivity and Regional Statistics from EEG for Early Stage Parkinson's Classification. MLSP Amarpal Sahota, Amber Roguski, Matthew W. Jones, Zahraa S. Abdallah, Raúl Santos-Rodríguez
2024	J	`jnl`	Investigating Brain Connectivity and Regional Statistics from EEG for early stage Parkinson's Classification. CoRR Amarpal Sahota, Amber Roguski, Matthew W. Jones, Zahraa S. Abdallah, Raúl Santos-Rodríguez
2024	A	`conf`	Learning Confidence Bounds for Classification with Imbalanced Data. ECAI Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Raúl Santos-Rodríguez, Dario García-García
2024	J	`jnl`	Learning Confidence Bounds for Classification with Imbalanced Data. CoRR Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Raúl Santos-Rodríguez, Dario García-García
2024	J	`jnl`	Safe and Robust Reinforcement Learning: Principles and Practice. CoRR Taku Yamagata, Raúl Santos-Rodríguez
2024	J	`jnl`	The Effect of Perceptual Metrics on Music Representation Learning for Genre Classification. CoRR Tashi Namgyal, Alexander Hepburn, Raúl Santos-Rodríguez, Valero Laparra, Jesus Malo
2024	J	`jnl`	Towards Personalised Patient Risk Prediction Using Temporal Hospital Data Trajectories. CoRR Thea Barnes, Enrico Werner, Jeffrey N. Clark, Raúl Santos-Rodríguez
2024	—	`conf`	TraCE: Trajectory Counterfactual Explanation Scores. NLDL Jeffrey Nicholas Clark, Edward Alexander Small, Nawid Keshtmand, Michelle Wing Lam Wan, Elena Fillola Mayoral, Enrico Werner, Christopher P. Bourdeaux, Raúl Santos-Rodríguez
2024	—	`conf`	Typicality-based point OOD detection with contrastive learning. NLDL Nawid Keshtmand, Raúl Santos-Rodríguez, Jonathan Lawry
2024	J	`jnl`	Using Similarity to Evaluate Factual Consistency in Summaries. CoRR Yuxuan Ye, Edwin Simpson, Raúl Santos-Rodríguez
2023	J	`jnl`	An active semi-supervised deep learning model for human activity recognition. J. Ambient Intell. Humaniz. Comput. Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach, Ian Craddock
2023	J	`jnl`	CATS: Cloud-native time-series data annotation tool for intensive care. SoftwareX Marceli Wac, Raúl Santos-Rodríguez, Christopher J. McWilliams, Christopher P. Bourdeaux
2023	J	`jnl`	Capturing Requirements for a Data Annotation Tool for Intensive Care: Experimental User-Centered Design Study. CoRR Marceli Wac, Raúl Santos-Rodríguez, Christopher J. McWilliams, Christopher P. Bourdeaux
2023	J	`jnl`	Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2023	J	`jnl`	Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making. Int. J. Hum. Comput. Stud. Katarzyna Stawarz, Dmitri S. Katz, Amid Ayobi, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2023	J	`jnl`	Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse. CoRR Edward A. Small, Jeffrey N. Clark, Christopher J. McWilliams, Kacper Sokol, Jeffrey Chan, Flora D. Salim, Raúl Santos-Rodríguez
2023	J	`jnl`	Data is Overrated: Perceptual Metrics Can Lead Learning in the Absence of Training Data. CoRR Tashi Namgyal, Alexander Hepburn, Raúl Santos-Rodríguez, Valero Laparra, Jesus Malo
2023	J	`jnl`	Disentangling the Link Between Image Statistics and Human Perception. CoRR Alexander Hepburn, Valero Laparra, Raúl Santos-Rodríguez, Jesús Malo
2023	J	`jnl`	Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. CoRR Weisong Yang, Rafael Poyiadzi, Niall Twomey, Raúl Santos-Rodríguez
2023	J	`jnl`	Identification, explanation and clinical evaluation of hospital patient subtypes. CoRR Enrico Werner, Jeffrey N. Clark, Ranjeet S. Bhamber, Michael Ambler, Christopher P. Bourdeaux, Alexander Hepburn, Christopher J. McWilliams, Raúl Santos-Rodríguez
2023	J	`jnl`	LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient Representations. CoRR Ahmed Khalil, Robert J. Piechocki, Raúl Santos-Rodríguez
2023	J	`jnl`	MIDI-Draw: Sketching to Control Melody Generation. CoRR Tashi Namgyal, Peter A. Flach, Raúl Santos-Rodríguez
2023	J	`jnl`	Monitoring Sustainable Global Development Along Shared Socioeconomic Pathways. CoRR Michelle W. L. Wan, Jeffrey N. Clark, Edward A. Small, Elena Fillola Mayoral, Raúl Santos-Rodríguez
2023	—	`conf`	Multi-lingual agents through multi-headed neural networks. NLDL Jonathan D. Thomas, Raúl Santos-Rodríguez, Mihai Anca, Robert J. Piechocki
2023	J	`jnl`	Privacy in Multimodal Federated Human Activity Recognition. CoRR Alex Iacob, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville
2023	A*	`conf`	Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL. ICML Taku Yamagata, Ahmed Khalil, Raúl Santos-Rodríguez
2023	A	`conf`	Reconciling Training and Evaluation Objectives in Location Agnostic Surrogate Explainers. CIKM Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Peter A. Flach, Raúl Santos-Rodríguez
2023	J	`jnl`	Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease. CoRR Maha M. Alwuthaynani, Zahraa S. Abdallah, Raúl Santos-Rodríguez
2023	J	`jnl`	Two-step counterfactual generation for OOD examples. CoRR Nawid Keshtmand, Raúl Santos-Rodríguez, Jonathan Lawry
2023	J	`jnl`	What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics. CoRR Tashi Namgyal, Alexander Hepburn, Raúl Santos-Rodríguez, Valero Laparra, Jesus Malo
2023	—	`conf`	When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. PerCom Workshops Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
2023	J	`jnl`	When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. CoRR Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Weisong Yang, Peter A. Flach
2022	—	`ch.`	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 Weisong Yang, Rafael Poyiadzi, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey
2022	J	`jnl`	FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. CoRR Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
2022	J	`jnl`	FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency. Softw. Impacts Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
2022	—	`conf`	Hypothesis Testing for Class-Conditional Label Noise. ECML/PKDD (3) Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez
2022	A*	`conf`	On the relation between statistical learning and perceptual distances. ICLR Alexander Hepburn, Valero Laparra, Raúl Santos-Rodríguez, Johannes Ballé, Jesus Malo
2022	J	`jnl`	Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL. CoRR Taku Yamagata, Ahmed Khalil, Raúl Santos-Rodríguez
2022	A	`conf`	Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers. BMVC Ricardo Kleinlein, Alexander Hepburn, Raúl Santos-Rodríguez, Fernando Fernández Martínez
2022	J	`jnl`	Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers. CoRR Ricardo Kleinlein, Alexander Hepburn, Raúl Santos-Rodríguez, Fernando Fernández Martínez
2022	J	`jnl`	Self-Supervised Multimodal Fusion Transformer for Passive Activity Recognition. CoRR Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville
2022	—	`conf`	Self-Supervised WiFi-Based Activity Recognition. GLOBECOM (Workshops) Mohammud Junaid Bocus, Hok-Shing Lau, Ryan McConville, Robert J. Piechocki, Raúl Santos-Rodríguez
2022	J	`jnl`	Self-play learning strategies for resource assignment in Open-RAN networks. Comput. Networks Xiaoyang Wang, Jonathan D. Thomas, Robert J. Piechocki, Shipra Kapoor, Raúl Santos-Rodríguez, Arjun Parekh
2022	J	`jnl`	Self-supervised multimodal fusion transformer for passive activity recognition. IET Wirel. Sens. Syst. Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville
2022	—	`conf`	Temporal Self-Supervised Learning for RSSI-based Indoor Localization. ICC Jonas Paulavicius, Seifallah Jardak, Ryan McConville, Robert J. Piechocki, Raúl Santos-Rodríguez
2022	—	`conf`	The Weak Supervision Landscape. PerCom Workshops Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
2022	J	`jnl`	The Weak Supervision Landscape. CoRR Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesús Cid-Sueiro, Miquel Perelló-Nieto, Peter A. Flach, Raúl Santos-Rodríguez
2022	—	`conf`	Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach. NLDL Jonas Schulz, Raúl Santos-Rodríguez, Rafael Poyiadzi
2022	—	`conf`	Understanding Reinforcement Learning Based Localisation as a Probabilistic Inference Algorithm. ICANN (2) Taku Yamagata, Raúl Santos-Rodríguez, Robert J. Piechocki, Peter A. Flach
2022	—	`conf`	Understanding the Properties and Limitations of Contrastive Learning for Out-of-Distribution Detection. ICPR Workshops (1) Nawid Keshtmand, Raúl Santos-Rodríguez, Jonathan Lawry
2022	J	`jnl`	Understanding the properties and limitations of contrastive learning for Out-of-Distribution detection. CoRR Nawid Keshtmand, Raúl Santos-Rodríguez, Jonathan Lawry
2022	J	`jnl`	What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components. CoRR Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach
2021	J	`jnl`	Classifier Calibration: How to assess and improve predicted class probabilities: a survey. CoRR Telmo de Menezes e Silva Filho, Hao Song, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Meelis Kull, Peter A. Flach
2021	J	`jnl`	Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies. Proc. ACM Hum. Comput. Interact. Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2021	B	`conf`	Conditional t-SNE: More informative t-SNE embeddings. DSAA Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021	J	`jnl`	Conditional t-SNE: more informative t-SNE embeddings. Mach. Learn. Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021	B	`conf`	Explainers in the Wild: Making Surrogate Explainers Robust to Distortions Through Perception. ICIP Alexander Hepburn, Raúl Santos-Rodríguez
2021	J	`jnl`	Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception. CoRR Alexander Hepburn, Raúl Santos-Rodríguez
2021	J	`jnl`	Human Activity Recognition Based on Dynamic Active Learning. IEEE J. Biomed. Health Informatics Haixia Bi, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Peter A. Flach
2021	—	`conf`	Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning. IUI Workshops Amid Ayobi, Katarzyna Stawarz, Dmitri S. Katz, Paul Marshall, Taku Yamagata, Raúl Santos-Rodríguez, Peter A. Flach, Aisling Ann O'Kane
2021	J	`jnl`	Multi-lingual agents through multi-headed neural networks. CoRR Jonathan D. Thomas, Raúl Santos-Rodríguez, Robert J. Piechocki, Mihai Anca
2021	—	`conf`	On the Selection of Loss Functions Under Known Weak Label Models. ICANN (2) Daniel Bacaicoa-Barber, Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro
2021	J	`jnl`	On the overlooked issue of defining explanation objectives for local-surrogate explainers. CoRR Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki
2021	J	`jnl`	On the relation between statistical learning and perceptual distances. CoRR Alexander Hepburn, Valero Laparra, Raúl Santos-Rodríguez, Johannes Ballé, Jesús Malo
2021	J	`jnl`	Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills. CoRR Taku Yamagata, Ryan McConville, Raúl Santos-Rodríguez
2021	J	`jnl`	Self-Supervised WiFi-Based Activity Recognition. CoRR Hok-Shing Lau, Ryan McConville, Mohammud Junaid Bocus, Robert J. Piechocki, Raúl Santos-Rodríguez
2021	J	`jnl`	Self-play Learning Strategies for Resource Assignment in Open-RAN Networks. CoRR Xiaoyang Wang, Jonathan D. Thomas, Robert J. Piechocki, Shipra Kapoor, Raúl Santos-Rodríguez, Arjun Parekh
2021	J	`jnl`	Statistical Hypothesis Testing for Class-Conditional Label Noise. CoRR Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez
2021	J	`jnl`	Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach. CoRR Jonas Schulz, Rafael Poyiadzi, Raúl Santos-Rodríguez
2021	J	`jnl`	Understanding surrogate explanations: the interplay between complexity, fidelity and coverage. CoRR Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki
2021	J	`jnl`	Vesta: A digital health analytics platform for a smart home in a box. Future Gener. Comput. Syst. Ryan McConville, Gareth Archer, Ian Craddock, Michal Kozlowski, Robert J. Piechocki, James Pope, Raúl Santos-Rodríguez
2020	—	`conf`	Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. AAI4H@ECAI Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey
2020	J	`jnl`	Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. CoRR Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raúl Santos-Rodríguez, James Selwood, Niall Twomey
2020	—	`conf`	Enforcing perceptual consistency on Generative Adversarial Networks by using the Normalised Laplacian Pyramid Distance. NLDL Alexander Hepburn, Valero Laparra, Ryan McConville, Raúl Santos-Rodríguez
2020	C	`conf`	FACE: Feasible and Actionable Counterfactual Explanations. AIES Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodríguez, Tijl De Bie, Peter A. Flach
2020	J	`jnl`	FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. J. Open Source Softw. Kacper Sokol, Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raúl Santos-Rodríguez, Peter A. Flach
2020	J	`jnl`	Information Theory Measures via Multidimensional Gaussianization. CoRR Valero Laparra, Juan Emmanuel Johnson, Gustau Camps-Valls, Raúl Santos-Rodríguez, Jesus Malo
2020	J	`jnl`	Information Theory in Density Destructors. CoRR Juan Emmanuel Johnson, Valero Laparra, Gustau Camps-Valls, Raúl Santos-Rodríguez, Jesús Malo
2020	B	`conf`	Low Cost Localisation in Residential Environments using High Resolution CIR Information. GLOBECOM Mohammud Junaid Bocus, Jonas Paulavicius, Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki
2020	—	`conf`	Model-Based Reinforcement Learning for Type 1 Diabetes Blood Glucose Control. AAI4H@ECAI Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
2020	J	`jnl`	Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control. CoRR Taku Yamagata, Aisling Ann O'Kane, Amid Ayobi, Dmitri S. Katz, Katarzyna Stawarz, Paul Marshall, Peter A. Flach, Raúl Santos-Rodríguez
2020	B	`conf`	N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. ICPR Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock
2020	A	`conf`	Neural ODEs with Stochastic Vector Field Mixtures. ECAI Niall Twomey, Michal Kozlowski, Raúl Santos-Rodríguez
2020	B	`conf`	Perceptnet: A Human Visual System Inspired Neural Network For Estimating Perceptual Distance. ICIP Alexander Hepburn, Valero Laparra, Jesús Malo, Ryan McConville, Raúl Santos-Rodríguez
2020	C	`conf`	Polsar Image Classification via Robust Low-Rank Feature Extraction and Markov Random Field. IGARSS Haixia Bi, Raúl Santos-Rodríguez, Peter A. Flach
2020	J	`jnl`	Recycling weak labels for multiclass classification. Neurocomputing Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Dario García-García, Jesús Cid-Sueiro
2020	B	`conf`	Translation Resilient Opportunistic WiFi Sensing. ICPR Mohammud Junaid Bocus, Wenda Li, Jonas Paulavicius, Ryan McConville, Raúl Santos-Rodríguez, Kevin Chetty, Robert J. Piechocki
2019	Misc	`conf`	Active Learning with Label Proportions. ICASSP Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
2019	J	`jnl`	Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information. CoRR Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2019	J	`jnl`	Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance. CoRR Alexander Hepburn, Valero Laparra, Ryan McConville, Raúl Santos-Rodríguez
2019	J	`jnl`	FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency. CoRR Kacper Sokol, Raúl Santos-Rodríguez, Peter A. Flach
2019	—	`conf`	Location Anomalies Detection for Connected and Autonomous Vehicles. CAVS Xiaoyang Wang, Ioannis Mavromatis, Andrea Tassi, Raúl Santos-Rodríguez, Robert J. Piechocki
2019	J	`jnl`	Location Anomalies Detection for Connected and Autonomous Vehicles. CoRR Xiaoyang Wang, Ioannis Mavromatis, Andrea Tassi, Raúl Santos-Rodríguez, Robert J. Piechocki
2019	J	`jnl`	N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. CoRR Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock
2019	J	`jnl`	Neural ODEs with stochastic vector field mixtures. CoRR Niall Twomey, Michal Kozlowski, Raúl Santos-Rodríguez
2019	J	`jnl`	Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback. CoRR Taku Yamagata, Raúl Santos-Rodríguez, Ryan McConville, Atis Elsts
2019	J	`jnl`	Ordinal Regression as Structured Classification. CoRR Niall Twomey, Rafael Poyiadzi, Callum Mann, Raúl Santos-Rodríguez
2019	J	`jnl`	PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance. CoRR Alexander Hepburn, Valero Laparra, Jesús Malo, Ryan McConville, Raúl Santos-Rodríguez
2019	J	`jnl`	Scalable and efficient learning from crowds with Gaussian processes. Inf. Fusion Pablo Morales-Alvarez, Pablo Ruiz, Raúl Santos-Rodríguez, Rafael Molina, Aggelos K. Katsaggelos
2019	J	`jnl`	Sensor Modalities and Fusion for Robust Indoor Localisation. EAI Endorsed Trans. Ambient Syst. Michal Kozlowski, Raúl Santos-Rodríguez, Robert J. Piechocki
2019	J	`jnl`	bLIMEy: Surrogate Prediction Explanations Beyond LIME. CoRR Kacper Sokol, Alexander Hepburn, Raúl Santos-Rodríguez, Peter A. Flach
2018	—	`conf`	Data fusion for robust indoor localisation in digital health. WCNC Workshops Michal Kozlowski, Dallan Byrne, Raúl Santos-Rodríguez, Robert J. Piechocki
2018	B	`conf`	Efficient approximate representations for computationally expensive features. ESANN Raúl Santos-Rodríguez, Niall Twomey
2018	J	`jnl`	Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks. CoRR Michal Kozlowski, Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki
2018	J	`jnl`	Label Propagation for Learning with Label Proportions. CoRR Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
2018	—	`conf`	Label Propagation for Learning with Label proportions. MLSP Rafael Poyiadzi, Raúl Santos-Rodríguez, Niall Twomey
2018	—	`conf`	Ordinal Label Proportions. ECML/PKDD (1) Rafael Poyiadzi, Raúl Santos-Rodríguez, Tijl De Bie
2018	B	`conf`	Person Identification and Discovery With Wrist Worn Accelerometer Data. ESANN Ryan McConville, Raúl Santos-Rodríguez, Niall Twomey
2018	—	`conf`	Proper Losses for Learning with Example-Dependent Costs. LIDTA@ECML/PKDD Alexander Hepburn, Ryan McConville, Raúl Santos-Rodríguez, Jesús Cid-Sueiro, Dario García-García
2018	J	`jnl`	SICA: subjectively interesting component analysis. Data Min. Knowl. Discov. Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2018	J	`jnl`	Signal-to-noise ratio in reproducing kernel Hilbert spaces. Pattern Recognit. Lett. Luis Gómez-Chova, Raúl Santos-Rodríguez, Gustau Camps-Valls
2018	—	`conf`	Understanding the quality of calibrations for indoor localisation. WF-IoT Ryan McConville, Dallan Byrne, Ian Craddock, Robert J. Piechocki, James Pope, Raúl Santos-Rodríguez
2017	B	`conf`	Adapting Supervised Classification Algorithms to Arbitrary Weak Label Scenarios. IDA Miquel Perelló-Nieto, Raúl Santos-Rodríguez, Jesús Cid-Sueiro
2017	B	`conf`	Hierarchical Novelty Detection. IDA Paolo Simeone, Raúl Santos-Rodríguez, Matt McVicar, Jefrey Lijffijt, Tijl De Bie
2017	—	`conf`	SPHERE in a Box: Practical and Scalable EurValve Activity Monitoring Smart Home Kit. LCN Workshops James Pope, Ryan McConville, Michal Kozlowski, Xenofon Fafoutis, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock
2016	B	`conf`	Informative data projections: a framework and two examples. ESANN Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, Bo Kang
2015	C	`conf`	Spatial/spectral information trade-off in hyperspectral images. IGARSS Valero Laparra, Raúl Santos-Rodríguez
2014	—	`conf`	Consistency of Losses for Learning from Weak Labels. ECML/PKDD (1) Jesús Cid-Sueiro, Dario García-García, Raúl Santos-Rodríguez
2013	J	`jnl`	Understanding Effects of Subjectivity in Measuring Chord Estimation Accuracy. IEEE ACM Trans. Audio Speech Lang. Process. Yizhao Ni, Matt McVicar, Raúl Santos-Rodríguez, Tijl De Bie
2012	—	`conf`	Classifier-based affinities for clustering sets of vectors. MLSP Dario García-García, Raúl Santos-Rodríguez, Emilio Parrado-Hernández
2012	J	`jnl`	Cost-Sensitive Sequences of Bregman Divergences. IEEE Trans. Neural Networks Learn. Syst. Raúl Santos-Rodríguez, Jesús Cid-Sueiro
2011	A*	`conf`	Risk-Based Generalizations of f-divergences. ICML Dario García-García, Ulrike von Luxburg, Raúl Santos-Rodríguez
2011	Misc	`conf`	Sphere packing for clustering sets of vectors in feature space. ICASSP Dario García-García, Raúl Santos-Rodríguez
2010	—	`conf`	Cost-Sensitive Feature Selection Based on the Set Covering Machine. ICDM Workshops Raúl Santos-Rodríguez, Dario García-García
2009	C	`conf`	Cost-Sensitive Classification Based on Bregman Divergences for Medical Diagnosis. ICMLA Raúl Santos-Rodríguez, Dario García-García, Jesús Cid-Sueiro
2009	—	`conf`	Cost-Sensitive Learning Based on Bregman Divergences. ECML/PKDD (1) Raúl Santos-Rodríguez, Alicia Guerrero-Curieses, Rocío Alaíz-Rodríguez, Jesús Cid-Sueiro
2009	J	`jnl`	Cost-sensitive learning based on Bregman divergences. Mach. Learn. Raúl Santos-Rodríguez, Alicia Guerrero-Curieses, Rocío Alaíz-Rodríguez, Jesús Cid-Sueiro
2009	C	`conf`	Spectral Clustering and Feature Selection for Microarray Data. ICMLA Dario García-García, Raúl Santos-Rodríguez