John Shawe-Taylor

Orcid: 0000-0002-2030-0073

Affiliations:
  • University College, London, UK


According to our database1, John Shawe-Taylor authored at least 296 papers between 1981 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

Legend:

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Online presence:

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Bibliography

2024
A Toolbox for Modelling Engagement with Educational Videos.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Seeking information about assistive technology: Exploring current practices, challenges, and the need for smarter systems.
Int. J. Hum. Comput. Stud., September, 2023

Model validation using mutated training labels: An exploratory study.
Neurocomputing, June, 2023

From fear to action: AI governance and opportunities for all.
Frontiers Comput. Sci., 2023

Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models.
CoRR, 2023

Social AI and the Challenges of the Human-AI Ecosystem.
CoRR, 2023

Exploration via Epistemic Value Estimation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Stability-based PAC-Bayes analysis for multi-view learning algorithms.
Inf. Fusion, 2022

Human-Centered Artificial Intelligence (Dagstuhl Seminar 22262).
Dagstuhl Reports, 2022

TransductGAN: a Transductive Adversarial Model for Novelty Detection.
CoRR, 2022

Controlling Confusion via Generalisation Bounds.
CoRR, 2022

Correlation Based Semantic Transfer with Application to Domain Adaptation.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments.
Proceedings of the 15th International Conference on Educational Data Mining, 2022

Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
Proceedings of the CHIIR '22: ACM SIGIR Conference on Human Information Interaction and Retrieval, Regensburg, Germany, March 14, 2022

Chaining Value Functions for Off-Policy Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Road map for research on responsible artificial intelligence for development (AI4D) in African countries: The case study of agriculture.
Patterns, 2021

Tighter Risk Certificates for Neural Networks.
J. Mach. Learn. Res., 2021

PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses.
Entropy, 2021

Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems.
CoRR, 2021

Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution.
CoRR, 2021

An AI-based Learning Companion Promoting Lifelong Learning Opportunities for All.
CoRR, 2021

Progress in Self-Certified Neural Networks.
CoRR, 2021

Learning PAC-Bayes Priors for Probabilistic Neural Networks.
CoRR, 2021

PEEK: A Large Dataset of Learner Engagement with Educational Videos.
CoRR, 2021

X5Learn: A Personalised Learning Companion at the Intersection of AI and HCI.
Proceedings of the IUI '21: 26th International Conference on Intelligent User Interfaces, 2021

2020
Report on the WSDM 2020 workshop on state-based user modelling (SUM'20).
SIGIR Forum, 2020

Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy.
Neurocomputing, 2020

Upper and Lower Bounds on the Performance of Kernel PCA.
CoRR, 2020

A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings.
CoRR, 2020

VLEngagement: A Dataset of Scientific Video Lectures for Evaluating Population-based Engagement.
CoRR, 2020

Correlated Feature Selection with Extended Exclusive Group Lasso.
CoRR, 2020

SUM'20: State-based User Modelling.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

PAC-Bayes Analysis Beyond the Usual Bounds.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Adaptive Mechanism Design: Learning to Promote Cooperation.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Predicting Engagement in Video Lectures.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Towards an Integrative Educational Recommender for Lifelong Learners (Student Abstract).
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important.
NeuroImage, 2019

Towards an Integrative Educational Recommender for Lifelong Learners.
CoRR, 2019

Constructing Artificial Data for Fine-tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation.
CoRR, 2019

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

Deep Learning Enhanced Extended Depth-of-Field for Thick Blood-Film Malaria High-Throughput Microscopy.
CoRR, 2019

Perturbed Model Validation: A New Framework to Validate Model Relevance.
CoRR, 2019

2018
Interactional regions in cities: making sense of flows across networked systems.
Int. J. Geogr. Inf. Sci., 2018

A Balanced Route Design for Min-Max Multiple-Depot Rural Postman Problem (MMMDRPP): a police patrolling case.
Int. J. Geogr. Inf. Sci., 2018

A Tutorial on Canonical Correlation Methods.
ACM Comput. Surv., 2018

Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection.
CoRR, 2018

Faster Convergence & Generalization in DNNs.
CoRR, 2018

Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression.
CoRR, 2018

Improving Active Learning in Systematic Reviews.
CoRR, 2018

Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

PAC-Bayes bounds for stable algorithms with instance-dependent priors.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Empirical Risk Minimization Under Fairness Constraints.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017
High-probability minimax probability machines.
Mach. Learn., 2017

PAC-Bayes analysis of multi-view learning.
Inf. Fusion, 2017

A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Localized Lasso for High-Dimensional Regression.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Sparse Network Lasso for Local High-dimensional Regression.
CoRR, 2016

Neighborhood Sensitive Mapping for Zero-Shot Classification using Independently Learned Semantic Embeddings.
CoRR, 2016

Image Retrieval with a Bayesian Model of Relevance Feedback.
CoRR, 2016

Learning Shared Representations in Multi-task Reinforcement Learning.
CoRR, 2016

A multimodal multiple kernel learning approach to Alzheimer's disease detection.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Distributed variance regularized Multitask Learning.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Challenges in representation learning: A report on three machine learning contests.
Neural Networks, 2015

Sparse network-based models for patient classification using fMRI.
NeuroImage, 2015

Multivariate Effect Ranking via Adaptive Sparse PLS.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

2014
Correction to "SCoRS - A Method Based on Stability for Feature Selection and Mapping in Neuroimaging".
IEEE Trans. Medical Imaging, 2014

SCoRS - A Method Based on Stability for Feature Selection and Apping in Neuroimaging.
IEEE Trans. Medical Imaging, 2014

Discovering brain regions relevant to obsessive-compulsive disorder identification through bagging and transduction.
Medical Image Anal., 2014

Manifold-preserving graph reduction for sparse semi-supervised learning.
Neurocomputing, 2014

PAC-Bayes Analysis of Multi-view Learning.
CoRR, 2014

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood.
CoRR, 2014

Learning Non-Linear Feature Maps, With An Application To Representation Learning.
Proceedings of the 2nd International Conference on Learning Representations, 2014

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., 2014

Leveraging Clinical Data to Enhance Localization of Brain Atrophy.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2014

Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Deep-er Kernels.
Proceedings of the ICPRAM 2014, 2014

Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

2013
Tighter PAC-Bayes bounds through distribution-dependent priors.
Theor. Comput. Sci., 2013

Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria.
PLoS Comput. Biol., 2013

A Comparison of Relaxations of Multiset Cannonical Correlation Analysis and Applications
CoRR, 2013

Learning Non-Linear Feature Maps.
CoRR, 2013

Decombinator: a tool for fast, efficient gene assignment in T-cell receptor sequences using a finite state machine.
Bioinform., 2013

Sparse Network-Based Models for Patient Classification Using fMRI.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Stability-Based Multivariate Mapping Using SCoRS.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013


Smooth Operators.
Proceedings of the 30th International Conference on Machine Learning, 2013

Drug screening with Elastic-net multiple kernel learning.
Proceedings of the 13th IEEE International Conference on BioInformatics and BioEngineering, 2013

2012
PAC-Bayesian Inequalities for Martingales.
IEEE Trans. Inf. Theory, 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

PAC-bayes bounds with data dependent priors.
J. Mach. Learn. Res., 2012

Data dependent kernels in nearly-linear time.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Preface.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Forecasting foreign exchange rates using kernel methods.
Expert Syst. Appl., 2012

MahNMF: Manhattan Non-negative Matrix Factorization
CoRR, 2012

Voxel Selection in MRI through Bagging and Conformal Analysis: Application to Detection of Obsessive Compulsive Disorder.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

2011
Design and Generalization Analysis of Orthogonal Matching Pursuit Algorithms.
IEEE Trans. Inf. Theory, 2011

Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine.
NeuroImage, 2011

Neural prediction of higher-order auditory sequence statistics.
NeuroImage, 2011

Sparse canonical correlation analysis.
Mach. Learn., 2011

Improved Loss Bounds For Multiple Kernel Learning.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Employing The Complete Face in AVSR to Recover from Facial Occlusions.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Introduction to the Special Topic on Grammar Induction, Representation of Language and Language Learning.
J. Mach. Learn. Res., 2011

Preface.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

A review of optimization methodologies in support vector machines.
Neurocomputing, 2011

A Note on Improved Loss Bounds for Multiple Kernel Learning
CoRR, 2011

PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
CoRR, 2011

PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
CoRR, 2011

PAC-Bayesian Analysis of Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A New Feature Selection Method Based on Stability Theory - Exploring Parameters Space to Evaluate Classification Accuracy in Neuroimaging Data.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

2010
Prediction with the SVM Using Test Point Margins.
Proceedings of the Data Mining - Special Issue in Annals of Information Systems, 2010

A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems.
J. Signal Process. Syst., 2010

A kernel regression framework for SMT.
Mach. Transl., 2010

Decomposing the tensor kernel support vector machine for neuroscience data with structured labels.
Mach. Learn., 2010

Sparse Semi-supervised Learning Using Conjugate Functions.
J. Mach. Learn. Res., 2010

Regret Bounds for Gaussian Process Bandit Problems.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Content-based Image Retrieval with Multinomial Relevance Feedback.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Multiple Kernel Learning on the Limit Order Book.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Preface.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Pinview: Implicit Feedback in Content-Based Image Retrieval.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Gaussian Process Bandits for Tree Search
CoRR, 2010

Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Constructing Nonlinear Discriminants from Multiple Data Views.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Sensor placement and coordination via distributed multi-agent cooperative control.
Proceedings of the 3rd International Conference on Pervasive Technologies Related to Assistive Environments, 2010

Multivariate Bandits and Their Applications.
Proceedings of the Intelligent Information Processing V, 2010

Learning relevant eye movement feature spaces across users.
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, 2010

Data Dependent Priors in PAC-Bayes Bounds.
Proceedings of the 19th International Conference on Computational Statistics, 2010

Semi-supervised feature learning from clinical text.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

Distribution-Dependent PAC-Bayes Priors.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

A PAC-Bayes Bound for Tailored Density Estimation.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods.
Cambridge University Press, ISBN: 978-0-521-78019-3, 2010

2009
Can eyes reveal interest? Implicit queries from gaze patterns.
User Model. User Adapt. Interact., 2009

Efficient Sparse Kernel Feature Extraction Based on Partial Least Squares.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Guest editors' introduction: Special Issue from ECML PKDD 2009.
Mach. Learn., 2009

Convergence analysis of kernel Canonical Correlation Analysis: theory and practice.
Mach. Learn., 2009

Large-Margin Structured Prediction via Linear Programming.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

PAC-Bayes Analysis Of Maximum Entropy Classification.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Matching Pursuit Kernel Fisher Discriminant Analysis.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Guest editors' introduction: special issue of selected papers from ECML PKDD 2009.
Data Min. Knowl. Discov., 2009

Pattern analysis for the prediction of fungal pro-peptide cleavage sites.
Discret. Appl. Math., 2009

GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison.
Connect. Sci., 2009

Technical perspective - Machine learning for complex predictions.
Commun. ACM, 2009

Improving the Confidence of Machine Translation Quality Estimates.
Proceedings of Machine Translation Summit XII: Papers, 2009

Prior Knowledge in Learning Finite Parameter Spaces.
Proceedings of the Formal Grammar - 14th International Conference, 2009

Large-margin structural prediction via linear programming.
Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

Sentence-level confidence estimation for MT.
Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

2008
Responsive listening behavior.
Comput. Animat. Virtual Worlds, 2008

Using string kernels to identify famous performers from their playing style.
Intell. Data Anal., 2008

Kernel Regression Framework for Machine Translation: UCL System Description for WMT 2008 Shared Translation Task.
Proceedings of the Third Workshop on Statistical Machine Translation, 2008

Theory of matching pursuit.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Complexity of pattern classes and the Lipschitz property.
Theor. Comput. Sci., 2007

Unsupervised analysis of fMRI data using kernel canonical correlation.
NeuroImage, 2007

A Framework for Probability Density Estimation.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Margin based Transductive Graph Cuts using Linear Programming.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data.
J. Mach. Learn. Res., 2007

Information Retrieval by Inferring Implicit Queries from Eye Movements.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Gaussian Process Approximations of Stochastic Differential Equations.
Proceedings of the Gaussian Processes in Practice, 2007

Advanced learning algorithms for cross-language patent retrieval and classification.
Inf. Process. Manag., 2007

Synthesis of maximum margin and multiview learning using unlabeled data.
Neurocomputing, 2007

Kernel ellipsoidal trimming.
Comput. Stat. Data Anal., 2007

Variational Inference for Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Kernel Regression Based Machine Translation.
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2007

New feature selection frameworks in emotion recognition to evaluate the informative power of speech related features.
Proceedings of the 9th International Symposium on Signal Processing and Its Applications, 2007

Using Generalization Error Bounds to Train the Set Covering Machine.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

Using Image Stimuli to Drive fMRI Analysis.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

Approximate maximum margin algorithms with rules controlled by the number of mistakes.
Proceedings of the Machine Learning, 2007

2006
Kernel-Based Learning of Hierarchical Multilabel Classification Models.
J. Mach. Learn. Res., 2006

Using KCCA for Japanese-English cross-language information retrieval and document classification.
J. Intell. Inf. Syst., 2006

Tighter PAC-Bayes Bounds.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A probabilistic model for text kernels.
Proceedings of the Machine Learning, 2006

Constant Rate Approximate Maximum Margin Algorithms.
Proceedings of the Machine Learning: ECML 2006, 2006

The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces.
Proceedings of the Machine Learning: ECML 2006, 2006

A Correlation Approach for Automatic Image Annotation.
Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006

2005
On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA.
IEEE Trans. Inf. Theory, 2005

Comparison and fusion of multiresolution features for texture classification.
Pattern Recognit. Lett., 2005

PAC-Bayesian Compression Bounds on the Prediction Error of Learning Algorithms for Classification.
Mach. Learn., 2005

Efficient Computation of Gapped Substring Kernels on Large Alphabets.
J. Mach. Learn. Res., 2005

Two view learning: SVM-2K, Theory and Practice.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005


An Investigation of Feature Models for Music Genre Classification Using the Support Vector Classifier.
Proceedings of the ISMIR 2005, 2005

Learning hierarchical multi-category text classification models.
Proceedings of the Machine Learning, 2005

Analysis of Generic Perceptron-Like Large Margin Classifiers.
Proceedings of the Machine Learning: ECML 2005, 2005

Mixture of Vector Experts.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

2004
Canonical Correlation Analysis: An Overview with Application to Learning Methods.
Neural Comput., 2004

Texture Classification by Combining Wavelet and Contourlet Features.
Proceedings of the Structural, 2004

Support Vector Machine to Synthesise Kernels.
Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

Complexity of Pattern Classes and Lipschitz Property.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

Kernel Methods for Pattern Analysis.
Cambridge University Press, ISBN: 978-0-521-81397-6, 2004

Kernel Methods for Pattern Analysis.
Cambridge University Press, ISBN: 9780511809682, 2004

2003
The SVM With Uneven Margins and Chinese Document Categorization.
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation, 2003

Semi-Definite Programming by Perceptron Learning.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

The Set Covering Machine with Data-Dependent Half-Spaces.
Proceedings of the Machine Learning, 2003

Linear Programming Boosting for Uneven Datasets.
Proceedings of the Machine Learning, 2003

Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

When Is Small Beautiful?
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Refining Kernels for Regression and Uneven Classification Problems.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002
On the generalization of soft margin algorithms.
IEEE Trans. Inf. Theory, 2002

Covering numbers for support vector machines.
IEEE Trans. Inf. Theory, 2002

Wanda: a database of duplicated fish genes.
Nucleic Acids Res., 2002

Linear Programming Boosting via Column Generation.
Mach. Learn., 2002

The Set Covering Machine.
J. Mach. Learn. Res., 2002

Text Classification using String Kernels.
J. Mach. Learn. Res., 2002

Latent Semantic Kernels.
J. Intell. Inf. Syst., 2002

Boosting strategy for classification.
Intell. Data Anal., 2002

Kernel Methods for Document Filtering.
Proceedings of The Eleventh Text REtrieval Conference, 2002

Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

The Decision List Machine.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

String Kernels, Fisher Kernels and Finite State Automata.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

PAC-Bayes & Margins.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning Semantic Similarity.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Syllables and other String Kernel Extensions.
Proceedings of the Machine Learning, 2002

The Perceptron Algorithm with Uneven Margins.
Proceedings of the Machine Learning, 2002

On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum.
Proceedings of the Discovery Science, 5th International Conference, 2002

2001
Estimating the Support of a High-Dimensional Distribution.
Neural Comput., 2001

An Unsupervised Neural Network Approach to Profiling the Behavior of Mobile Phone Users for Use in Fraud Detection.
J. Parallel Distributed Comput., 2001

Neural Network Learning: Theoretical Foundation.
AI Mag., 2001

On the Concentration of Spectral Properties.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Spectral Kernel Methods for Clustering.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

On Kernel-Target Alignment.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Learning with the Set Covering Machine.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Composite Kernels for Hypertext Categorisation.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000
Enlarging the Margins in Perceptron Decision Trees.
Mach. Learn., 2000

Characterizing Graph Drawing with Eigenvectors.
J. Chem. Inf. Comput. Sci., 2000

Graph Colouring by Maximal Evidence Edge Adding.
Proceedings of the Practice and Theory of Automated Timetabling III, 2000

Text Classification using String Kernels.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Boosting the Margin Distribution.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2000

Direct Bayes Point Machines.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

A Column Generation Algorithm For Boosting.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Sparsity vs. Large Margins for Linear Classifiers.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

Generalisation Error Bounds for Sparse Linear Classifiers.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods.
Cambridge University Press, ISBN: 9780511801389, 2000

1999
Introducing the Special Issue of Machine Learning Selected from Papers Presented at the 1997 Conference on Computational Learning Theory, COLT'97.
Mach. Learn., 1999

Detection of fraud in mobile telecommunications.
Inf. Secur. Tech. Rep., 1999

The Entropy Regularization Information Criterion.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Support Vector Method for Novelty Detection.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Large Margin DAGs for Multiclass Classification.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Large Margin Trees for Induction and Transduction.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

Generalization Performance of Classifiers in Terms of Observed Covering Numbers.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Margin Distribution Bounds on Generalization.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

A multiplicative updating algorithm for training support vector machine.
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

Further Results on the Margin Distribution.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
Structural Risk Minimization Over Data-Dependent Hierarchies.
IEEE Trans. Inf. Theory, 1998

Special Issue of DAM on the Vapnik-chervonenkis Dimension.
Discret. Appl. Math., 1998

Classification Accuracy Based on Observed Margin.
Algorithmica, 1998

Optimizing Classifers for Imbalanced Training Sets.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Dynamically Adapting Kernels in Support Vector Machines.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

A Neural Accelerator for Graph Colouring Based on an Edge Adding Technique.
Proceedings of the International ICSC / IFAC Symposium on Neural Computation (NC 1998), 1998

Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

1997
A Sufficient Condition for Polynomial Distribution-dependent Learnability.
Discret. Appl. Math., 1997

Data-Dependent Structural Risk Minimization for Perceptron Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Parallel Graph colouring using FPGAs.
Proceedings of the Field-Programmable Logic and Applications, 7th International Workshop, 1997

Confidence Estimates of Classification Accuracy on New Examples.
Proceedings of the Computational Learning Theory, Third European Conference, 1997

A PAC Analysis of a Bayesian Estimator.
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

1996
A unifying framework for invariant pattern recognition.
Pattern Recognit. Lett., 1996

Learning in Stochastic Bit Stream Neural Networks.
Neural Networks, 1996

Representation Theory and Invariant Neural Networks.
Discret. Appl. Math., 1996

Fast String Matching in Stationary Ergodic Sources.
Comb. Probab. Comput., 1996

Valid Generalisation from Approximate Interpolation.
Comb. Probab. Comput., 1996

A recurrent network with stochastic weights.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996

Learning to Compress Ergodic Sources.
Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31, 1996

A Framework for Structural Risk Minimisation.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
Sample Sizes for Threshold Networks with Equivalences
Inf. Comput., April, 1995

On Specifying Boolean Functions by Labelled Examples.
Discret. Appl. Math., 1995

Generalisation of A Class of Continuous Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Generalisation Analysis for Classes of Continuous Neural Networks.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Neural networks for invariant pattern recognition.
Proceedings of the 3rd European Symposium on Artificial Neural Networks, 1995

Sample Sizes for Sigmoidal Neural Networks.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

The Complexity of Learning Minor Closed Graph Classes.
Proceedings of the Algorithmic Learning Theory, 6th International Conference, 1995

1994
Generating binary sequences for stochastic computing.
IEEE Trans. Inf. Theory, 1994

Fast String Matching using an <i> n </i> -gram Algorithm.
Softw. Pract. Exp., 1994

Homeomorphism of 2-Complexes is Graph Isomorphism Complete.
SIAM J. Comput., 1994

Coverings of complete bipartite graphs and associated structures.
Discret. Math., 1994

Molecular Graph Eigenvectors for Molecular Coordinates.
Proceedings of the Graph Drawing, DIMACS International Workshop, 1994

1993
Symmetries and discriminability in feedforward network architectures.
IEEE Trans. Neural Networks, 1993

Bounding Sample Size with the Vapnik-Chervonenkis Dimension.
Discret. Appl. Math., 1993

A Result of Vapnik with Applications.
Discret. Appl. Math., 1993

Using the Perceptron Algorithm to Find Consistent Hypotheses.
Comb. Probab. Comput., 1993

Valid generalisation of functions from close approximations on a sample.
Proceedings of the First European Conference on Computational Learning Theory, 1993

1992
An Approximate String-Matching Algorithm.
Theor. Comput. Sci., 1992

Classes of feedforward neural networks and their circuit complexity.
Neural Networks, 1992

Fast Multiple Keyword Searching.
Proceedings of the Combinatorial Pattern Matching, Third Annual Symposium, 1992

On Exact Specification by Examples.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1991
Threshold Network Learning in the Presence of Equivalences.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990
Linear programming algorithm for neural networks.
Neural Networks, 1990

The Learnability of Formal Concepts.
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

1988
Transformational theory of feedforward neural networks.
Neural Networks, 1988

1987
Information and its Relation to Formalisms for the Complexities of the Real World.
J. Inf. Technol., 1987

Distance-regularised graphs are distance-regular or distance-biregular.
J. Comb. Theory, Ser. B, 1987

Automorphism Groups of Primitive Distance-Bitransitive Graphs are Almost Simple.
Eur. J. Comb., 1987

1985
Distance-biregular graphs with 2-valent vertices and distance-regular line graphs.
J. Comb. Theory, Ser. B, 1985

1983
Edge-colorability of graph bundles.
J. Comb. Theory, Ser. B, 1983

1981
Search for minimal trivalent cycle permutation graphs with girth nine.
Discret. Math., 1981


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