People : jason : publications

Books

Léon Bottou and Olivier Chapelle and Dennis DeCoste and Jason Weston (editors): Large Scale Kernel Machines. MIT Press (2007) (link)

Articles and Conference Papers

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Corinna Cortes and Mehryar Mohri: Half Transductive Ranking. AISTATS (2010) (link)

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Kunihiko Sadamasa and Yanjun Qi and Olivier Chappel and Kilian Weinberger: Learning to Rank with (a lot of) Word Features. Information Retrieval Special Issue: Learning to Rank for IR (2009) (link)

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Kunihiko Sadamasa and Yanjun Qi and Corinna Cortes and Mehryar Mohri: Polynomial Semantic Indexing. Advances in Neural Information Processing Systems 22 (2009) (link)

Y. Bengio, J. Louradour and Ronan Collobert and Jason Weston: Curriculum Learning. Proceedings of the Twenty-sixth International Conference on Machine Learning (ICML 2009) (2009) (link)

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Corinna Cortes and Mehryar Mohri: Ranking with Half Transductive Models. NIPS Workshop on Advances in Ranking (2009)

Marina Spivak and Jason Weston and Leon Bottou, L. Kall, W. Stafford Noble: Improvements to the Percolator algorithm for peptide identification from shotgun proteomics data sets. Journal of Proteome Research (2009) (link)

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Kunihiko Sadamasa and Yanjun Qi and Olivier Chappel and Kilian Weinberger: Learning to Rank with Low Rank. SIGIR Workshop: Learning to Rank for IR (2009)

Bing Bai and Jason Weston and Ronan Collobert and David Grangier: Supervised Semantic Indexing. Proceedings of the 31st European Conference on Information Retrieval (ECIR09) (2009) (link)

Bing Bai and Jason Weston and David Grangier and Ronan Collobert and Kunihiko Sadamasa and Yanjun Qi and Olivier Chappel and Kilian Weinberger: Supervised Semantic Indexing. Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM09) (2009) (link)

Hossein Mobahi and Ronan Collobert and Jason Weston: Deep Learning from Temporal Coherence in Video. Proceedings of the Twenty-sixth International Conference on Machine Learning (ICML 2009) (2009) (link)

Karlen, Michael and Weston, Jason and Erkan, Ayse and Collobert, Ronan: Large Scale Manifold Transduction. Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008) (2008) (link)

Collobert, Ronan and Weston, Jason: A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning. Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008) (2008) (link)

Weston, Jason and Ratle, Frédéric and Collobert, Ronan: Deep Learning via Semi-Supervised Embedding. Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008) (2008) (link)

Weston, Jason: Large Scale Semi-Supervised Learning. Proceedings of NATO Advanced Study Institute on Mining Massive Data Sets for Security (2008) (link)

Ratle, Frederic and Weston, Jason and Miller, Matthew: Large-scale clustering through functional embedding. Machine Learning: ECML 2008 (2008) (link)

Melvin, Iain and Weston, Jason and Leslie, Christina and Noble, William Stafford: RANKPROP: a web server for protein remote homology detection. Bioinformatics (2008) (link)

Melvin, Iain and Weston, Jason and Leslie, Christina and Noble, William Stafford: Combining classifiers for improved classification of proteins from sequence or structure. BMC Bioinformatics (2008) (link)

Sonnenburg, Sören and Braun, Mikio L. and Ong, Cheng Soon and Bengio, Samy and Bottou, Léon and Holmes, Geoffrey and LeCun, Yann and Müller, Klaus-Robert and Pereira, Fernando and Rasmussen, Carl Edward, Rätsch, Gunnar and Schölkopf, Bernhard and Smola, Alexander and Vincent, Pascal and Weston, Jason and Williamson Robert: The Need for Open Source Software in Machine Learning. The Journal of Machine Learning Research (2007) (link)

Antoine Bordes and Léon Bottou and Patrick Gallinari and Jason Weston: Solving MultiClass Support Vector Machines with LaRank. Proceedings of the 24th International Machine Learning Conference (2007) (link)

Collobert, Ronan and Weston, Jason: Fast Semantic Extraction Using a Novel Neural Network Architecture. 45th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Accepted. (2007) (link)

Collobert, Ronan and Sinz, Fabian and Weston, Jason and Bottou, Léon: Trading Convexity for Scalability. Large Scale Kernel Machines (2007) (link)

Melvin, Iain and Ie, Eugene and Weston, Jason and Noble, William Stafford and Leslie, Christina: Multi-class protein classification using adaptive codes. Journal of Machine Learning Research (2007)

Cortes, Corinna and Mohri, Mehryar and Weston, Jason: A General Regression Framework for Learning String-to-String Mappings. Predicting Structured Data (2007) (link)

Lukas Kall and Jesse Canterbury and Jason Weston and William S. Noble and Michael J. MacCoss: Semi-Supervised Learning for Peptide Identification from Shotgun Proteomics Datasets. Nature Methods (2007) (link)

BakIr, Gökhan and Schölkopf, Bernhard and Weston, Jason: On the pre-image problem in kernel methods. Kernel Methods in Bioengineering, Signal and Image Processing (2007) (link)

Weston, Jason and BakIr, Goekhan and Bousquet, Olivier and Schölkopf, Bernhard and Mann, T. and Noble, William Stafford: Joint Kernel Maps. Predicting Structured Data (2007) (link)

Collobert, Ronan and Sinz, Fabian and Weston, Jason and Bottou, Léon: Large Scale Transductive SVMs. Journal of Machine Learning Research (2006) (link)

Melvin, Iain and Ie, Eugene and Kuang, Rui and Weston, Jason and Noble, William and Leslie, Christina: SVM-fold : a tool for discriminative multi-class protein fold and superfamily recognition. BMC Bioinformatics (2006) (link)

Lal, T. N. and Chapelle, Olivier and Weston, Jason and Elisseeff, Andre: Embedded Methods. Feature extraction, foundations and Applications (2006) (link)

Weston, Jason and Collobert, Ronan and Sinz, Fabian and Bottou, Léon and Vapnik, Vladimir: Inference with the Universum. Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006) (2006) (link)

Weston, Jason and Leslie, Christina and Ie, Eugene and Zhou, Dengyong and Elisseeff, Andre and Noble, William Stafford: Semi-supervised protein classification using cluster kernels. Semi-Supervised Learning (2006) (link)

Collobert, Ronan and Weston, Jason and Bottou, Léon: Trading Convexity for Scalability. Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006) (2006) (link)

Weston, Jason and Schölkopf, Bernhard and Bousquet, Olivier: Joint Kernel Maps. Proceedings of the 8th International Work-Conference on Artificial Neural Networks (Computational Intelligence and Bioinspired System) (2005) (link)

Cortes, Corinna and Mohri, Mehryar and Weston, Jason: A General Regression Technique for Learning Transductions. Proceedings of the Twenty-second International Conference on Machine Learning (ICML 2005) (2005) (link)

BakIr, Gökhan and Bottou, Léon and Weston, Jason: Breaking SVM Complexity with Cross-Training. Advances in Neural Information Processing Systems (2005) (link)

Ie, Eugene and Weston, Jason and Noble, William Stafford and Leslie, Christina: Multi-class protein fold recognition using adaptive codes. Proceedings of the Twenty-second International Conference on Machine Learning (ICML 2005) (2005) (link)

Noble, William Stafford and Kuang, Rui and Leslie, Christina and Weston, Jason: Identifying remote protein homologs by network propagation. FEBS Journal (2005) (link)

Weston, Jason and Bordes, Antoine and Bottou, Léon: Online (and Offline) on an Even Tighter Budget. Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, January 2005, Barbados (2005) (link)

Weston, Jason and Kuang, Rui and Leslie, Christina and Noble, William: Protein Ranking by Semi-Supervised Network Propagation. BMC Bioinformatics Special Issue (2005) (link)

Bordes, Antoine and Ertekin, Seyda and Weston, Jason and Bottou, Léon: Fast Kernel Classifiers with Online and Active Learning. Journal of Machine Learning Research (2005) (link)

Weston, Jason and Leslie, Christina and Ie, Eugene and Zhou, Dengyong and Elisseeff, Andre and Noble, William Stafford: Semi-supervised protein classification using cluster kernels. Bioinformatics (15) (2005) (link)

Kuang, Rui and Weston, Jason and Noble, William Stafford and Leslie, Christina: Motif-based protein ranking by network propagation. Bioinformatics (19) (2005) (link)

Weston, Jason and Elisseeff, Andre and Zhou, Dengyong and Leslie, Christina and W. S. Noble: Protein ranking: from local to global structure in the protein similarity network. Proceedings of the National Academy of Science (17) (2004) (link)

Leslie, Christina and Eskin, E and Cohen, A. and Weston, Jason and Noble, William Stafford: Mismatch string kernels for discriminative protein classification. Bioinformatics (4) (2004) (link)

Lal, T.N. and M. Schröder and T. Hinterberger and Weston, Jason and M. Bogdan and N. Birbaumer and Schölkopf, Bernhard: Support Vector Channel Selection in BCI. IEEE Transactions on Biomedical Engineering (6) (2004) (link)

Weston, Jason and Leslie, Christina and Zhou, Dengyong and Elisseeff, Andre and Noble, William: Semi-Supervised Protein Classification using Cluster Kernels. Advances in Neural Information Processing Systems (2004) (link)

Eichhorn, Jan and Tolias, Andreas and Zien, Alex and Kuss, Malte and Rasmussen, Carl and Weston, Jason and Logothetis, Nikos and Schölkopf, Bernhard: Prediction on Spike Data Using Kernel Algorithms. Advances in Neural Information Processing Systems (2004) (link)

Zhou, D. and Bousquet, Olivier and T.N. Lal and Weston, Jason and Schölkopf, Bernhard: Learning with Local and Global Consistency. Advances in Neural Information Processing Systems (2004)

Zhou, D. and Weston, Jason and A. Gretton and Bousquet, Olivier and Schölkopf, Bernhard: Ranking on Data Manifolds. Advances in Neural Information Processing Systems (2004) (link)

BakIr, Gökhan and Weston, Jason and Schölkopf, Bernhard: Learning to Find Pre-Images. Advances in Neural Information Processing Systems (2004) (link)

Weston, Jason and Pérez-Cruz, Fernando and Bousquet, Olivier and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics (6) (2003) (link)

Weston, Jason and Elisseeff, Andre and Schölkopf, Bernhard and M. Tipping: Use of the Zero-Norm with Linear Models and Kernel Methods. Journal of Machine Learning Research (7-8) (2003) (link)

Weston, Jason and Schölkopf, Bernhard and Eskin, Eleazar and Leslie, Christina and Noble, William: Dealing with large Diagonals in Kernel Matrices. Annals of the Institute of Statistical Mathematics (2) (2003) (link)

Weston, Jason and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard and Vapnik, Vladimir: Kernel Dependency Estimation.. Advances in Neural Information Processing Systems (2003) (link)

Mika, Sebastian and Rätsch, Gunnar and Weston, Jason and Schölkopf, Bernhard and A.J. Smola and K.-R. Müller: Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence (5) (2003) (link)

Chapelle, O. and Schölkopf, Bernhard and Weston, Jason: Semi-Supervised Learning through Principal Directions Estimation. ICML Workshop, The Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining (2003) (link)

Schölkopf, B. and I. Guyon and Weston, Jason: Statistical Learning and Kernel Methods in Bioinformatics. Artificial Intelligence and Heuristic Methods in Bioinformatics (2003)

Chapelle, O. and Weston, Jason and Schölkopf, Bernhard: Cluster Kernels for Semi-Supervised Learning.. Advances in Neural Information Processing Systems (2003) (link)

Leslie, C. and E. Eskin and Weston, Jason and W. S. Noble: Mismatch String Kernels for SVM Protein Classification.. Advances in Neural Information Processing Systems (2003) (link)

Pérez-Cruz, Fernando and Weston, Jason and Herrmann, Daniel and Schölkopf, Bernhard: Extension of the nu-SVM range for classification. Advances in Learning Theory: Methods, Models and Applications (2003) (link)

Guyon, Isabelle and Weston, Jason and Barnhill, Steven and Vapnik, Vladimir: Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning (2002) (link)

Schölkopf, B. and Weston, Jason and E. Eskin and Leslie, Christina and W.S. Noble: A kernel approach for learning from almost orthogonal patterns. 13th European Conference on Machine Learning (ECML 2002) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'2002), Helsinki (2002)

Pavlidis, P. and Weston, Jason and Cai, J. and Noble, W.S.: Learning Gene Functional Classifications from Multiple Data Types. Journal of Computational Biology (2) (2002)

Elisseeff, Andre and Weston, Jason: A kernel method for multi-labeled classification. Advances in Neural Information Processing Systems (2001) (link)

Weston, Jason and Herbrich, Ralf: Adaptive margin Support Vector machines. Advances in Large Margin Classifiers (2000) (link)

Chapelle, Olivier and Vapnik, Vladimir and Weston, Jason: Transductive Inference for Estimating Values of Functions. Advances in Neural Information Processing Systems 12 (2000) (link)

Weston, Jason and S. Mukherjee and Chapelle, Olivier and M. Pontil and T. Poggio and Vapnik, Vladimir: Feature Selection for SVMs. Advances in Neural Information Processing Systems (2000) (link)

Mika, Sebastian and Rätsch, Gunnar and Weston, Jason and Schölkopf, Bernhard and A.J. Smola and K.-R. Müller: Invariant feature extraction and classification in kernel spaces.. Advances in Neural Information Processing Systems (2000) (link)

Chapelle, O. and Weston, Jason and Bottou, Léon and Vapnik, Vladimir: Vicinal Risk Minimization. Advances in Neural Information Processing Systems (2000) (link)

Weston, Jason and Watkins, Chris: Multi-class Support Vector Machines. Proceedings ESANN (1999) (link)

Mika, Sebastian and Rätsch, Gunnar and Weston, Jason and Schölkopf, Bernhard and K.-R. Müller: Fisher discriminant analysis with kernels.. Neural Networks for Signal Processing (1999)

Weston, Jason and Gammerman, A. and Stitson, M.O. and Vapnik, V. and Vovk, V. and Watkins, C.: Support vector density estimation. Advances in kernel methods: support vector learning table of contents (1999) (link)

Herbrich, Ralf and Weston, Jason: Adaptive margin support vector machines for classification. Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470) (1999) (link)

Weston, Jason: Leave-One-Out Support Vector Machines. Proceedings of the International Joint Conference o (1999) (link)

Stitson, Mark and Gammerman, Alex and Vapnik, Vladimir and Vovk, Volodya and Watkins, Chris and Weston, Jason: Support Vector Regression with {ANOVA} Decomposition Kernels. Advances in Kernel Methods --- Support Vector Learning (1999)

Pavlidis, Paul and Weston, Jason and Cai, J. and Grundy, William: Gene functional classification from heterogeneous data. Proceedings of the Fifth International Conference on Computational Molecular Biology (00)

Tech Reports

Weston, Jason and Schölkopf, Bernhard and Bousquet, Olivier and Mann and Noble: Joint Kernel Maps. Max-Planck-Institute for Biological Cybernetics (131) (2004) (link)

Weston, Jason and BakIr, Gökhan: Fast Binary and Multi-Output Reduced Set Selection. Max-Planck-Institute for Biological Cybernetics (132) (2004) (link)

Zhou, D. and Weston, Jason and A. Gretton and Bousquet, Olivier and Schölkopf, Bernhard: Ranking on Data Manifolds. Max Planck Institute for Biological Cybernetics (113) (2003)

Weston, Jason and Christina Leslie and Andre Elisseeff and William Stafford Noble: Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms. Max-Planck-Institute for Biological Cybernetics (111) (2003)

Zhou, D. and Bousquet, Olivier and T.N. Lal and Weston, Jason and Schölkopf, Bernhard: Learning with Local and Global Consistency. Max Planck Institute for Biological Cybernetics (112) (2003) (link)

Lal, Navin and Schröder, Michael and Hinterberger, Thilo and Weston, Jason and Bogdan, Martin and Birbaumer, Niels and Schölkopf, Bernhard: Support Vector Channel Selection in BCI. Max Planck Institute for Biological Cybernetics (120) (2003) (link)

Weston, Jason and Pérez-Cruz, Fernando and Bousquet, Olivier and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard: Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design. (2002) (link)

Weston, Jason and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard and Vapnik, Vladimir: Kernel Dependency Estimation. Max Planck Institute for Biological Cybernetics (98) (2002) (link)

Weston, Jason and Pérez-Cruz, Fernando and Bousquet, Olivier and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard: KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug design -- Binding to Thrombin. (2001) (link)

Weston, Jason and Chapelle, O. and Guyon,I.: Data cleaning algorithms with applications to micro-array experiments. Biowulf Technologies (2001)

Weston, Jason and Elisseeff, Andre and Schölkopf, Bernhard: Use of the L_0-norm with linear models and kernel methods. Biowulf Technologies (2001)

Saunders, Craig and Stitson, Mark and Weston, Jason and Bottou, Léon and Schölkopf, Bernhard and Smola, Alex: Support Vector Machine Reference Manual. University of London (CSD-TR-98-03) (1998) (link)

Theses

Weston, Jason: Extensions to the Support Vector Method. Royal Holloway, University of London (1999) (link)