John Shawe-Taylor

ORCID

Publication Activity (10 Years)

Years Active: 1981-2024
Publications (10 Years): 84

Top Venues

Publications

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)
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
Exploration via Epistemic Value Estimation. CoRR (2023)
Dino Pedreschi, Luca Pappalardo, Ricardo Baeza-Yates, Albert-László Barabási, Frank Dignum, Virginia Dignum, Tina Eliassi-Rad, Fosca Giannotti, János Kertész, Alistair Knott, Yannis E. Ioannidis, Paul Lukowicz, Andrea Passarella, Alex 'Sandy' Pentland, John Shawe-Taylor, Alessandro Vespignani
Social AI and the Challenges of the Human-AI Ecosystem. CoRR (2023)
Jamie Danemayer, Cathy Holloway, Youngjun Cho, Nadia Berthouze, Aneesha Singh, William Bhot, Ollie Dixon, Marko Grobelnik, John Shawe-Taylor
Seeking information about assistive technology: Exploring current practices, challenges, and the need for smarter systems. Int. J. Hum. Comput. Stud. 177 (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)
Kevin Baum, Joanna Bryson, Frank Dignum, Virginia Dignum, Marko Grobelnik, Holger H. Hoos, Morten Irgens, Paul Lukowicz, Catelijne Muller, Francesca Rossi, John Shawe-Taylor, Andreas Theodorou, Ricardo Vinuesa
From fear to action: AI governance and opportunities for all. Frontiers Comput. Sci. 5 (2023)
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
Exploration via Epistemic Value Estimation. AAAI (2023)
Jie M. Zhang, Mark Harman, Benjamin Guedj, Earl T. Barr, John Shawe-Taylor
Model validation using mutated training labels: An exploratory study. Neurocomputing 539 (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)
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
Chaining Value Functions for Off-Policy Learning. AAAI (2022)
Shiliang Sun, Mengran Yu, John Shawe-Taylor, Liang Mao
Stability-based PAC-Bayes analysis for multi-view learning algorithms. Inf. Fusion (2022)
Wendy E. Mackay, John Shawe-Taylor, Frank van Harmelen
Human-Centered Artificial Intelligence (Dagstuhl Seminar 22262). Dagstuhl Reports 12 (6) (2022)
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
Chaining Value Functions for Off-Policy Learning. CoRR (2022)
Reuben Adams, John Shawe-Taylor, Benjamin Guedj
Controlling Confusion via Generalisation Bounds. 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)
Florina-Cristina Calnegru, John Shawe-Taylor, Iasonas Kokkinos, Razvan Pascanu
Correlation Based Semantic Transfer with Application to Domain Adaptation. ICONIP (1) (2022)
Najiba Toron, Janaina Mourão-Miranda, John Shawe-Taylor
TransductGAN: a Transductive Adversarial Model for Novelty Detection. CoRR (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)
Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses. Entropy 23 (10) (2021)
Arthur Gwagwa, Emre Kazim, Patti Kachidza, Airlie Hilliard, Kathleen Siminyu, Matthew Smith, John Shawe-Taylor
Road map for research on responsible artificial intelligence for development (AI4D) in African countries: The case study of agriculture. Patterns 2 (12) (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)
Tobias Baumann, Thore Graepel, John Shawe-Taylor
Adaptive Mechanism Design: Learning to Promote Cooperation. IJCNN (2020)
Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor
Predicting Engagement in Video Lectures. CoRR (2020)
Jun Yamada, John Shawe-Taylor, Zafeirios Fountas
Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning. 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)
Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
Upper and Lower Bounds on the Performance of Kernel PCA. CoRR (2020)
Luca Oneto, Michele Donini, Massimiliano Pontil, John Shawe-Taylor
Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy. Neurocomputing 416 (2020)
Yuxin Sun, Benny Chain, Samuel Kaski, John Shawe-Taylor
Correlated Feature Selection with Extended Exclusive Group Lasso. CoRR (2020)
Jun Yamada, John Shawe-Taylor, Zafeirios Fountas
Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning. IJCNN (2020)
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
PAC-Bayes Analysis Beyond the Usual Bounds. 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)
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
PAC-Bayes Analysis Beyond the Usual Bounds. NeurIPS (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)
Maxime Haddouche, Benjamin Guedj, Omar Rivasplata, John Shawe-Taylor
PAC-Bayes unleashed: generalisation bounds with unbounded losses. CoRR (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)
Gaurav Singh, Zahra Sabet, John Shawe-Taylor, James Thomas
Constructing Artificial Data for Fine-tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation. CoRR (2019)
Michele Donini, João M. Monteiro, Massimiliano Pontil, Tim Hahn, Andreas J. Fallgatter, John Shawe-Taylor, Janaina Mourão Miranda
Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important. NeuroImage 195 (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)
Jie M. Zhang, Earl T. Barr, Benjamin Guedj, Mark Harman, John Shawe-Taylor
Perturbed Model Validation: A New Framework to Validate Model Relevance. CoRR (2019)
Biobele J. Brown, Alexander A. Przybylski, Petru Manescu, Fabio Caccioli, Gbeminiyi Oyinloye, Muna Elmi, Michael J. Shaw, Vijay Pawar, Remy Claveau, John Shawe-Taylor, Mandayam A. Srinivasan, Nathaniel K. Afolabi, Adebola E. Orimadegun, Wasiu A. Ajetunmobi, Francis Akinkunmi, Olayinka Kowobari, Kikelomo Osinusi, Felix O. Akinbami, Samuel Omokhodion, Wuraola A. Shokunbi, Ikeoluwa Lagunju, Olugbemiro Sodeinde, Delmiro Fernandez-Reyes
Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data. CoRR (2019)
Petru Manescu, Lydia Neary-Zajiczek, Michael J. Shaw, Muna Elmi, Remy Claveau, Vijay Pawar, John Shawe-Taylor, Iasonas Kokkinos, Mandayam A. Srinivasan, Ikeoluwa Lagunju, Olugbemiro Sodeinde, Biobele J. Brown, Delmiro Fernandez-Reyes
Deep Learning Enhanced Extended Depth-of-Field for Thick Blood-Film Malaria High-Throughput Microscopy. CoRR (2019)
Seth Nabarro, Tristan Fletcher, John Shawe-Taylor
Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression. CoRR (2018)
Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil
Empirical Risk Minimization Under Fairness Constraints. NeurIPS (2018)
Gaurav Singh, James Thomas, John Shawe-Taylor
Improving Active Learning in Systematic Reviews. CoRR (2018)
Huanfa Chen, Tao Cheng, John Shawe-Taylor
A Balanced Route Design for Min-Max Multiple-Depot Rural Postman Problem (MMMDRPP): a police patrolling case. Int. J. Geogr. Inf. Sci. 32 (1) (2018)
Omar Rivasplata, Emilio Parrado-Hernández, John Shawe-Taylor, Shiliang Sun, Csaba Szepesvári
PAC-Bayes bounds for stable algorithms with instance-dependent priors. CoRR (2018)
Gaurav Singh, John Shawe-Taylor
Faster Convergence & Generalization in DNNs. CoRR (2018)
Gaurav Singh, James Thomas, Iain James Marshall, John Shawe-Taylor, Byron C. Wallace
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding. CoRR (2018)
Fabio S. Ferreira, Maria J. Rosa, Michael Moutoussis, Ray Dolan, John Shawe-Taylor, John Ashburner, Janaina Mourão Miranda
Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships. PRNI (2018)
Omar Rivasplata, Csaba Szepesvári, John Shawe-Taylor, Emilio Parrado-Hernández, Shiliang Sun
PAC-Bayes bounds for stable algorithms with instance-dependent priors. NeurIPS (2018)
Tobias Baumann, Thore Graepel, John Shawe-Taylor
Adaptive Mechanism Design: Learning to Promote Cooperation. CoRR (2018)
Viivi Uurtio, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor, Delmiro Fernandez-Reyes, Juho Rousu
A Tutorial on Canonical Correlation Methods. ACM Comput. Surv. 50 (6) (2018)
Luke R. Harries, Suyi Zhang, Geoffroy Dubourg-Felonneau, James H. R. Farmery, Jonathan Sinai, Belle Taylor, Nirmesh Patel, John W. Cassidy, John Shawe-Taylor, Harry W. Clifford
Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection. CoRR (2018)
Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil
Empirical Risk Minimization under Fairness Constraints. CoRR (2018)
Kira Kempinska, Paul A. Longley, John Shawe-Taylor
Interactional regions in cities: making sense of flows across networked systems. Int. J. Geogr. Inf. Sci. 32 (7) (2018)
Gaurav Singh, James Thomas, Iain James Marshall, John Shawe-Taylor, Byron C. Wallace
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding. EMNLP (2018)
Shiliang Sun, John Shawe-Taylor, Liang Mao
PAC-Bayes analysis of multi-view learning. Inf. Fusion 35 (2017)
Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski
Localized Lasso for High-Dimensional Regression. AISTATS (2017)
Gaurav Singh, Iain James Marshall, James Thomas, John Shawe-Taylor, Byron C. Wallace
A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation. CIKM (2017)
Viivi Uurtio, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor, Delmiro Fernandez-Reyes, Juho Rousu
A Tutorial on Canonical Correlation Methods. CoRR (2017)
Simon Cousins, John Shawe-Taylor
High-probability minimax probability machines. Mach. Learn. 106 (6) (2017)
Michele Donini, João M. Monteiro, Massimiliano Pontil, John Shawe-Taylor, Janaina Mourão Miranda
A multimodal multiple kernel learning approach to Alzheimer's disease detection. MLSP (2016)
Gaurav Singh, Fabrizio Silvestri, John Shawe-Taylor
Neighborhood Sensitive Mapping for Zero-Shot Classification using Independently Learned Semantic Embeddings. CoRR (2016)
Diana Borsa, Thore Graepel, John Shawe-Taylor
Learning Shared Representations in Multi-task Reinforcement Learning. CoRR (2016)
Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski
Sparse Network Lasso for Local High-dimensional Regression. CoRR (2016)
Dorota Glowacka, Yee Whye Teh, John Shawe-Taylor
Image Retrieval with a Bayesian Model of Relevance Feedback. CoRR (2016)
Guy Lever, John Shawe-Taylor, Ronnie Stafford, Csaba Szepesvári
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning. AAAI (2016)
Michele Donini, David Martínez-Rego, Martin Goodson, John Shawe-Taylor, Massimiliano Pontil
Distributed variance regularized Multitask Learning. IJCNN (2016)
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-Hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Zhang Chuang, Yoshua Bengio
Challenges in representation learning: A report on three machine learning contests. Neural Networks 64 (2015)
Joao M. Monteiro, Anil Rao, John Ashburner, John Shawe-Taylor, Janaina Mourão Miranda
Multivariate Effect Ranking via Adaptive Sparse PLS. PRNI (2015)
Maria J. Rosa, Liana Catarina Lima Portugal, Tim Hahn, Andreas J. Fallgatter, Marta I. Garrido, John Shawe-Taylor, Janaina Mourão Miranda
Sparse network-based models for patient classification using fMRI. NeuroImage 105 (2015)
Emilio Parrado-Hernández, Vanessa Gómez-Verdejo, Manel Martínez-Ramón, John Shawe-Taylor, Pino Alonso, Jesús Pujol, José M. Menchón, Narcís Cardoner, Carles Soriano-Mas
Discovering brain regions relevant to obsessive-compulsive disorder identification through bagging and transduction. Medical Image Anal. 18 (3) (2014)
Sohan Seth, John Shawe-Taylor, Samuel Kaski
Retrieval of Experiments by Efficient Estimation of Marginal Likelihood. CoRR (2014)
Shiliang Sun, John Shawe-Taylor
PAC-Bayes Analysis of Multi-view Learning. CoRR (2014)
Dimitris Athanasakis, John Shawe-Taylor, Delmiro Fernandez-Reyes
Learning Non-Linear Feature Maps, With An Application To Representation Learning. ICLR (Workshop Poster) (2014)
Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. NIPS (2014)
Zakria Hussain, Arto Klami, Jussi Kujala, Alex Po Leung, Kitsuchart Pasupa, Peter Auer, Samuel Kaski, Jorma Laaksonen, John Shawe-Taylor
PinView: Implicit Feedback in Content-Based Image Retrieval. CoRR (2014)
Jane M. Rondina, Tim Hahn, Leticia de Oliveira, Andre F. Marquand, Thomas Dresler, Thomas Leitner, Andreas J. Fallgatter, John Shawe-Taylor, Janaina Mourão Miranda
SCoRS - A Method Based on Stability for Feature Selection and Apping in Neuroimaging. IEEE Trans. Medical Imaging 33 (1) (2014)
Jane M. Rondina, Tim Hahn, Leticia de Oliveira, Andre F. Marquand, Thomas Dresler, Thomas Leitner, Andreas J. Fallgatter, John Shawe-Taylor, Janaina Mourão Miranda
Correction to "SCoRS - A Method Based on Stability for Feature Selection and Mapping in Neuroimaging". IEEE Trans. Medical Imaging 33 (3) (2014)
Shiliang Sun, Zakria Hussain, John Shawe-Taylor
Manifold-preserving graph reduction for sparse semi-supervised learning. Neurocomputing 124 (2014)
John Shawe-Taylor
Deep-er Kernels. ICPRAM (2014)
João M. Monteiro, Anil Rao, John Ashburner, John Shawe-Taylor, Janaina Mourão Miranda
Leveraging Clinical Data to Enhance Localization of Brain Atrophy. MLINI@NIPS (2014)
Niclas Thomas, Katharine Best, Mattia Cinelli, Shlomit Reich-Zeliger, Hilah Gal, Eric Shifrut, Asaf Madi, Nir Friedman, John Shawe-Taylor, Benny Chain
Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinform. 30 (22) (2014)
Sohan Seth, John Shawe-Taylor, Samuel Kaski
Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods. ICONIP (2) (2014)
Steffen Grünewälder, Arthur Gretton, John Shawe-Taylor
Smooth Operators. ICML (3) (2013)
Kitsuchart Pasupa, Zakria Hussain, John Shawe-Taylor, Peter Willett
Drug screening with Elastic-net multiple kernel learning. BIBE (2013)
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-Hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
Challenges in Representation Learning: A report on three machine learning contests. CoRR (2013)

John Shawe-Taylor.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

John Shawe-Taylor