Jason Weston

Jason Weston is a research scientist at Google NY since July 2009. He earned his PhD in machine learning at Royal Holloway, University of London and at AT&T Research in Red Bank, NJ (advisor: V. Vapnik) in 2000. From 2000 to 2002, he was a research scientist at Biowulf technologies, New York. From 2002 to 2003 he was a research scientist at the Max Planck Institute for Biological Cybernetics, Tuebingen, Germany. From 2003 to June 2009 he was a research staff member at NEC Labs America, Princeton. Jason Weston's interests are in statistical machine learning and its application, particularly to text, audio and images.

Google Publications

A Semantic Matching Energy Function for Learning with Multi-relational Data

Xavier Glorot, Antoine Bordes, Jason Weston, Yoshua Bengio

International Conference on Learning Representations (2013)
A Semantic Matching Energy Function for Learning with Multi-relational Data

Antoine Bordes, Xavier Glorot, Jason Weston

Special Issue on Learning Semantics in Machine Learning Journal (2013) (to appear)
Affinity Weighted Embedding

Jason Weston, Ron Weiss, Hector Yee

International Conference on Learning Representations (2013)
Deep Learning via Semi-Supervised Embedding

Jason Weston, Frederic Ratle, Hossein Mobahi, Ronan Collobert

Neural Networks Tricks of the Trade, Reloaded, Springer (2013)
Label Partitioning for Sublinear Ranking

Jason Weston, Ameesh Makadia, Hector Yee

International Conference on Machine Learning (2013) (to appear)
Learning Semantic Representations Of Objects And Their Parts.

G Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio

Special Issue on Learning Semantics in Machine Learning Journal (2013) (to appear)
A unified multitask architecture for predicting local protein properties

Yanjun Qi, Merja Osh, Jason Weston, William Stafford Noble

PLoS ONE (2012) (to appear)
Joint Image and Word Sense Discrimination For Image Retrieval

Aurelien Lucchi, Jason Weston

ECCV (2012)
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing.

Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio

AISTATS (2012)
Latent Collaborative Retrieval

Jason Weston, Chong Wang, Ron Weiss, Adam Berenzweig

International Conference on Machine Learning (2012)
Latent Structured Ranking

Jason Weston, John Blitzer

UAI (2012)
Learning improved linear transforms for speech recognition

Andrew Senior, Youngmin Cho, Jason Weston

ICASSP, IEEE (2012)
Detecting remote evolutionary relationships among proteins by large-scale semantic embedding

Iain Melvin, Jason Weston, Christina Leslie, William Stafford Noble

PLoS Computational Biology (2011)
Large-Scale Music Annotation and Retrieval: Learning to Rank in Joint Semantic Spaces.

Jason Weston, Samy Bengio, Philippe Hamel

Journal of New Music Research (2011)
Learning Structured Embeddings of Knowledge Bases

Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio

Proceedings of the 25th Conference on Artificial Intelligence (AAAI) (2011)
Wsabie: Scaling Up To Large Vocabulary Image Annotation

Jason Weston, Samy Bengio, Nicolas Usunier

Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI (2011)
Half Transductive Ranking

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri

Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010)
Label Embedding Trees for Large Multi-Class Tasks

Samy Bengio, Jason Weston, David Grangier

Neural Information Processing Systems (NIPS) (2010)
Label Ranking under Ambiguous Supervision: An Application for Learning Semantic Correspondences

Nicolas Usunier, Antoine Bordes, Jason Weston

ICML, ICML (2010)
Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings

Jason Weston, Samy Bengio, Nicolas Usunier

European Conference on Machine Learning (2010)
Large scale image annotation: learning to rank with joint word-image embeddings

Jason Weston, Samy Bengio, Nicolas Usunier

Machine Learning, vol. 81, Issue 1 (2010), pp. 21
Natural Language Processing (almost) from Scratch

Ronan Collobert, Jason Weston, Leon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel Kuksa

Journal of Machine Learning Research (2010)
Semi-Supervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction.

Pavel Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston

ECML (2010)
Semi-Supervised Multi-Task Learning for Predicting Interactions between HIV-1 and Human Proteins

Yanjun Qi, Oznur Tastan, Jaime Carbonell, Judith Klein-Seetharaman, Jason Weston

ECCB (2010)
Towards Understanding Situated Natural Language

Antoine Bordes, Nicolas Usunier, Jason Weston

Artificial Intelligence and Statistics (AISTATS) (2010)
Polynomial semantic indexing

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri

Advances in Neural Information Processing Systems (NIPS 2009), MIT Press

Previous Publications

A User’s Guide to Support Vector Machines

Asa Ben-Hur, Jason Weston

Data Mining Techniques for the Life Sciences, Springer (2009)
Curriculum Learning

J. Louradour Y. Bengio, Ronan Collobert, Jason Weston

Proceedings of the Twenty-sixth International Conference on Machine Learning (ICML 2009)
Deep Learning from Temporal Coherence in Video

Hossein Mobahi, Ronan Collobert, Jason Weston

Proceedings of the Twenty-sixth International Conference on Machine Learning (ICML 2009)
Improvements to the Percolator algorithm for peptide identification from shotgun proteomics data sets

Marina Spivak, Jason Weston, W. Stafford Noble Leon Bottou, L. Kall

Journal of Proteome Research (2009)
Semisupervised Neural Networks for Efﬁcient Hyperspectral Image Classiﬁcation

Frederic Ratle, Gustavo Camps-Valls, Jason Weston

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2009)
Supervised Semantic Indexing

Bing Bai, Jason Weston, Ronan Collobert, David Grangier

Proceedings of the 31st European Conference on Information Retrieval (ECIR09), Toulouse, France (2009)
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning

Ronan Collobert, Jason Weston

Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008), IMLS/ICML
Combining classifiers for improved classification of proteins from sequence or structure

Iain Melvin, Jason Weston, Christina Leslie, William Stafford Noble

BMC Bioinformatics (2008)
Deep Learning via Semi-Supervised Embedding

Jason Weston, Frédéric Ratle, Ronan Collobert

Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008), IMLS/ICML
Large Scale Manifold Transduction

Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert

Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML 2008), IMLS/ICML
Large Scale Semi-Supervised Learning

Jason Weston

Proceedings of NATO Advanced Study Institute on Mining Massive Data Sets for Security, IOS Press (2008)
Large-scale clustering through functional embedding

Frederic Ratle, Jason Weston, Matthew Miller

Machine Learning: ECML 2008
RANKPROP: a web server for protein remote homology detection

Iain Melvin, Jason Weston, Christina Leslie, William Stafford Noble

Bioinformatics (2008)
A General Regression Framework for Learning String-to-String Mappings

Corinna Cortes, Mehryar Mohri, Jason Weston

Predicting Structured Data, The MIT Press (2007)
Fast Semantic Extraction Using a Novel Neural Network Architecture

Ronan Collobert, Jason Weston

45th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. (2007)
Joint Kernel Maps

Jason Weston, Goekhan BakIr, Olivier Bousquet, Bernhard Schölkopf, T. Mann, William Stafford Noble

Predicting Structured Data, M.I.T. Press (2007)
Large Scale Kernel Machines

L\'{e}on Bottou, Olivier Chapelle, Dennis DeCoste, Jason Weston

MIT Press, Cambridge, MA (2007)
Multi-class protein classification using adaptive codes

Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina Leslie

Journal of Machine Learning Research, vol. 8 (2007), pp. 1557-1581
On the pre-image problem in kernel methods

Gökhan Bakir, Bernhard Schölkopf, Jason Weston

Kernel Methods in Bioengineering, Signal and Image Processing, Idea Group Inc., http://www.idea-group.com 701 E. Chocolate Avenue Suite 200 Hershey, PA 17033, USA. (2007), -na-
SVM-fold: a tool for discriminative multi-class protein fold and superfamily recognition

Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, William Stafford Noble, Christina Leslie

BMC Bioinformatics (2007)
Semi-Supervised Learning for Peptide Identification from Shotgun Proteomics Datasets

Lukas Kall, Jesse Canterbury, Jason Weston, William S. Noble, Michael J. MacCoss

Nature Methods (2007)
Solving MultiClass Support Vector Machines with LaRank

Antoine Bordes, L\'{e}on Bottou, Patrick Gallinari, Jason Weston

Proceedings of the 24th International Machine Learning Conference, OmniPress, Corvallis, Oregon (2007), pp. 89-96
The Need for Open Source Software in Machine Learning

Soren Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoff Holmes, Yann LeCun, Klaus-Robert Mueller, Fernando Pereira, Carl-Edward Rasmussen, Gunnar Raetsch, Bernhard Schoelkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert C. Williamson

Journal of Machine Learning Research, vol. 8 (2007), pp. 2443-2466
Trading Convexity for Scalability

Ronan Collobert, Fabian Sinz, Jason Weston, L\'{e}on Bottou

Large Scale Kernel Machines, MIT Press, Cambridge, MA. (2007), pp. 301-320
Embedded Methods

T. N. Lal, Olivier Chapelle, Jason Weston, Andre Elisseeff

Feature extraction, foundations and Applications, Springer-Verlag, Berlin/Heidelberg, Germany (2006), pp. 137-165
Inference with the Universum

Jason Weston, Ronan Collobert, Fabian Sinz, L\'{e}on Bottou, Vladimir Vapnik

Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006), IMLS/ICML
Large Scale Transductive SVMs

Ronan Collobert, Fabian Sinz, Jason Weston, L\'{e}on Bottou

Journal of Machine Learning Research, vol. 7 (2006), pp. 1687-1712
Semi-supervised protein classification using cluster kernels

Jason Weston, Christina Leslie, Eugene Ie, William Stafford Noble

Semi-Supervised Learning, MIT Press (2006), pp. 329-346
Trading Convexity for Scalability

Ronan Collobert, Jason Weston, L\'{e}on Bottou

Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006), IMLS/ICML
A General Regression Technique for Learning Transductions

Corinna Cortes, Mehryar Mohri, Jason Weston

Proceedings of the Twenty-Second International Conference on Machine Learning (ICML 2005), Bonn, Germany
Breaking SVM Complexity with Cross-Training

Gökhan Bakir, Leon Bottou, Jason Weston

Advances in Neural Information Processing Systems, MIT Press (2005), pp. 81-88
Fast Kernel Classifiers with Online and Active Learning

Antoine Bordes, Seyda Ertekin, Jason Weston, L\'{e}on Bottou

Journal of Machine Learning Research, vol. 6 (2005), pp. 1579-1619
Identifying remote protein homologs by network propagation

William Stafford Noble, Rui Kuang, Christina Leslie, Jason Weston

FEBS Journal, vol. 272 (2005), pp. 5119
Joint Kernel Maps

Jason Weston, Bernhard Schölkopf, Olivier Bousquet

Proceedings of the 8th International Work-Conference on Artificial Neural Networks (Computational Intelligence and Bioinspired System), Springer-Verlag, Berlin Heidelberg, Germany (2005), pp. 176-191
Motif-based protein ranking by network propagation

Rui Kuang, Jason Weston, William Stafford Noble, Christina Leslie

Bioinformatics, vol. 21 (2005), pp. 3711-3718
Multi-class protein fold recognition using adaptive codes

Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie

Proceedings of the 22nd international conference on Machine learning (2005), pp. 329-336
Online (and Offline) on an Even Tighter Budget

Jason Weston, Antoine Bordes, L\'{e}on Bottou

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, January 2005, Barbados, Society for Artificial Intelligence and Statistics, pp. 413-420
Protein Ranking by Semi-Supervised Network Propagation

Jason Weston, Rui Kuang, Christina Leslie, William Noble

BMC Bioinformatics Special Issue (2005)
Semi-supervised protein classification using cluster kernels

Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, Andr, William Stafford Noble

Bioinformatics, vol. 21 (2005), pp. 3241-3247
Fast Binary and Multi-Output Reduced Set Selection

Jason Weston, Gökhan Bakir

Max-Planck-Institute for Biological Cybernetics, Max-Planck-Institute for Biological Cybernetics (2004)
Learning to Find Pre-Images

Gökhan Bakir, Jason Weston, Bernhard Schölkopf

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2004), pp. 449-456
Learning with Local and Global Consistency

D. Zhou, Olivier Bousquet, T.N. Lal, Jason Weston, Bernhard Schölkopf

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2004), pp. 321-328
Mismatch string kernels for discriminative protein classification

Christina Leslie, E Eskin, A. Cohen, Jason Weston, William Stafford Noble

Bioinformatics, vol. 20 (2004), pp. 467-476
Prediction on Spike Data Using Kernel Algorithms

Jan Eichhorn, Andreas Tolias, Alex Zien, Malte Kuss, Carl Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2004), pp. 1367-1374
Protein ranking: from local to global structure in the protein similarity network

Jason Weston, Andre Elisseeff, Dengyong Zhou, Christina Leslie, W. S. Noble

Proceedings of the National Academy of Science, vol. 101 (2004), pp. 6559-6563
Ranking on Data Manifolds

D. Zhou, Jason Weston, A. Gretton, Olivier Bousquet, Bernhard Schölkopf

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2004), pp. 169-176
Semi-Supervised Protein Classification using Cluster Kernels

Jason Weston, Christina Leslie, Dengyong Zhou, Andre Elisseeff, William Noble

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2004), pp. 595-602
Support Vector Channel Selection in BCI

T.N. Lal, M. Schroeder, T. Hinterberger, Jason Weston, M. Bogdan, N. Birbaumer, Bernhard Schölkopf

IEEE Transactions on Biomedical Engineering, vol. 51 (2004), pp. 1003-1010
Cluster Kernels for Semi-Supervised Learning

O. Chapelle, Jason Weston, Bernhard Schölkopf

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2003), pp. 585-592
Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, A.J. Smola, Klaus-Robert Müller

IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25 (2003), pp. 623-628
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller

IEEE Trans. Pattern Anal. Mach. Intell., vol. 25 (2003), pp. 623-633
Dealing with large Diagonals in Kernel Matrices

Jason Weston, Bernhard Schölkopf, Eleazar Eskin, Christina Leslie, William Noble

Annals of the Institute of Statistical Mathematics, vol. 55 (2003), pp. 391-408
Extension of the nu-SVM range for classification

Fernando Pérez-Cruz, Jason Weston, Daniel Herrmann, Bernhard Schölkopf

Advances in Learning Theory: Methods, Models and Applications, IOS Press, Amsterdam (2003), pp. 179-196
Feature selection and transduction for prediction of molecular bioactivity for drug design

Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, Andre Elisseeff, Bernhard Schölkopf

Bioinformatics, vol. 19 (2003), pp. 764-771
Kernel Dependency Estimation

Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2003), pp. 873-880
Learning with Local and Global Consistency

D. Zhou, Olivier Bousquet, T.N. Lal, Jason Weston, Bernhard Schölkopf

Max Planck Institute for Biological Cybernetics, Max Planck Institute for Biological Cybernetics (2003)
Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms

Jason Weston, Christina Leslie, Andre Elisseeff, William Stafford Noble

Max-Planck-Institute for Biological Cybernetics, MPI (2003), pp. 9
Mismatch String Kernels for SVM Protein Classification

C. Leslie, E. Eskin, Jason Weston, W. S. Noble

Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, USA (2003), pp. 1441 - 1448
Ranking on Data Manifolds

D. Zhou, Jason Weston, A. Gretton, Olivier Bousquet, Bernhard Schölkopf

Max Planck Institute for Biological Cybernetics, Max Planck Institute for Biological Cybernetics (2003)
Semi-Supervised Learning through Principal Directions Estimation

O. Chapelle, Bernhard Schölkopf, Jason Weston

ICML Workshop, The Continuum from Labeled to Unlabeled Data in Machine Learnin & Data Mining (2003)
Statistical Learning and Kernel Methods in Bioinformatics

B. Sch\, I. Guyon, Jason Weston

Artificial Intelligence and Heuristic Methods in Bioinformatics, IOS Press, Amsterdam, The Netherlands (2003), pp. 1-21
Support Vector Channel Selection in BCI

Navin Lal, Michael Schröder, Thilo Hinterberger, Jason Weston, Martin Bogdan, Niels Birbaumer, Bernhard Schölkopf

Max Planck Institute for Biological Cybernetics, Max Planck Institute for Biological Cybernetics (2003)
Use of the Zero-Norm with Linear Models and Kernel Methods

Jason Weston, Bernhard Schölkopf, Andre Elisseeff, M. Tipping

Journal of Machine Learning Research, vol. 3 (2003), pp. 1439-1461
A kernel approach for learning from almost orthogonal patterns

B. Sch\, Jason Weston, E. Eskin, Christina Leslie, W.S. Noble

13th European Conference on Machine Learning (ECML 2002) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'2002), Helsinki, Springer, Berlin, pp. 511-528
Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design

Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, Andre Elisseeff, Bernhard Schölkopf

Tuebingen Univ. (2002)
Gene Selection for Cancer Classification using Support Vector Machines

Isabelle Guyon, Jason Weston, Steven Barnhill, Vladimir Vapnik

Machine Learning (2002)
Learning Gene Functional Classifications from Multiple Data Types

P. Pavlidis, Jason Weston, J. Cai, W.S. Noble

Journal of Computational Biology, vol. 9 (2002), pp. 401-411
A kernel method for multi-labeled classification

Andre Elisseeff, Jason Weston

Advances in Neural Information Processing Systems, vol. 14 (2001)
Data cleaning algorithms with applications to micro-array experiments

Jason Weston, O. Chapelle, I. Guyon

Biowulf Technologies, Biowulf (2001)
Gene functional classification from heterogeneous data

Paul Pavlidis, Jason Weston, J. Cai, William Grundy

Proceedings of the Fifth International Conference on Computational Molecular Biology (2001), pp. 242-248
KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug design - Binding to Thrombin

Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, Andre Elisseeff, Bernhard Schölkopf

BIOwulf (2001)
Kernel methods for multi-labelled classification and categorical regression problems

Andre Elisseeff, Jason Weston

Biowulf Technologies, New York (2001)
Adaptive margin Support Vector machines

Jason Weston, Ralf Herbrich

Advances in Large Margin Classifiers, MIT Press, Cambridge, MA (2000), pp. 281-295
Feature Selection for SVMs

Jason Weston, S. Mukherjee, Olivier Chapelle, M. Pontil, T. Poggio, Vladimir Vapnik

Advances in Neural Information Processing Systems (2000)
Transductive Inference for Estimating Values of Functions

Olivier Chapelle, Vladimir Vapnik, Jason Weston

Advances in Neural Information Processing Systems 12, MIT press (2000)
Vicinal Risk Minimization

O. Chapelle, Jason Weston, L\'{e}on Bottou, Vladimir Vapnik

Advances in Neural Information Processing Systems (2000)
Adaptive margin support vector machines for classification

Ralf Herbrich, Jason Weston

Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470), vol. 2 (1999)
Extensions to the Support Vector Method

Jason Weston

Ph.D. Thesis, Tuebingen Univ. (1999)
Invariant Feature Extraction and Classification in Kernel Spaces

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller

NIPS (1999), pp. 526-532
Leave-One-Out Support Vector Machines

Jason Weston

Proceedings of the International Joint Conference on Artificial Intelligence, Sweden (1999)
Multi-class Support Vector Machines

Jason Weston, Chris Watkins

Proceedings ESANN, D Facto, Brussels (1999)
Support Vector Regression with ANOVA Decomposition Kernels

Mark Stitson, Alex Gammerman, Vladimir Vapnik, Volodya Vovk, Chris Watkins, Jason Weston

Advances in Kernel Methods -- Support Vector Learning, MIT Press, Cambridge, MA (1999), pp. 285-292
Support vector density estimation

Jason Weston, A. Gammerman, M.O. Stitson, V. Vapnik, V. Vovk, C. Watkins

Advances in kernel methods: support vector learning table of contents (1999), pp. 293-305
Multi-class Support Vector Machines

Jason Weston, Chris Watkins

Department of Computer Science, Royal Holloway, University of London, Egham, TW20 0EX, UK (1998)
Density Estimation using SV Machines

Jason Weston, Alex Gammerman, Mark Stitson, Vladimir Vapnik, Volodya Vovk, Chris Watkins

Royal Holloway, University of London, Egham, UK (1997)
Support vector regression with ANOVA decomposition kernels

Mark Stitson, Alex Gammerman, Vladimir Vapnik, Volodya Vovk, Chris Watkins, Jason Weston

Royal Holloway, University of London (1997)

Jason Weston

Co-Authors

Google Publications

Previous Publications