Jason Weston

Xavier Glorot, Antoine Bordes, Jason Weston, Yoshua Bengio: A Semantic Matching Energy Function for Learning with Multi-relational Data. CoRR abs/1301.3485 (2013)

Jason Weston, Ron Weiss, Hector Yee: Affinity Weighted Embedding. CoRR abs/1301.4171 (2013)

Antoine Bordes, Nicolas Usunier, Alberto García-Durán, Jason Weston, Oksana Yakhnenko: Irreflexive and Hierarchical Relations as Translations. CoRR abs/1304.7158 (2013)

Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio: Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing. Journal of Machine Learning Research - Proceedings Track 22: 127-135 (2012)

Aurélien Lucchi, Jason Weston: Joint Image and Word Sense Discrimination for Image Retrieval. ECCV (1) 2012: 130-143

Andrew W. Senior, Youngmin Cho, Jason Weston: Learning improved linear transforms for speech recognition. ICASSP 2012: 1957-1960

Jason Weston, Chong Wang, Ron Weiss, Adam Berenzweig: Latent Collaborative Retrieval. ICML 2012

Jason Weston, John Blitzer: Latent Structured Ranking. UAI 2012: 903-913

Jason Weston, Chong Wang, Ron Weiss, Adam Berenzweig: Latent Collaborative Retrieval. CoRR abs/1206.4603 (2012)

Jason Weston, John Blitzer: Latent Structured Ranking. CoRR abs/1210.4914 (2012)

Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel P. Kuksa: Natural Language Processing (Almost) from Scratch. Journal of Machine Learning Research 12: 2493-2537 (2011)

Iain Melvin, Jason Weston, William Stafford Noble, Christina S. Leslie: Detecting Remote Evolutionary Relationships among Proteins by Large-Scale Semantic Embedding. PLoS Computational Biology 7(1) (2011)

Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio: Learning Structured Embeddings of Knowledge Bases. AAAI 2011

Jason Weston, Samy Bengio, Nicolas Usunier: WSABIE: Scaling Up to Large Vocabulary Image Annotation. IJCAI 2011: 2764-2770

Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel P. Kuksa: Natural Language Processing (almost) from Scratch. CoRR abs/1103.0398 (2011)

Jason Weston, Samy Bengio, Philippe Hamel: Large-Scale Music Annotation and Retrieval: Learning to Rank in Joint Semantic Spaces. CoRR abs/1105.5196 (2011)

Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio: Towards Open-Text Semantic Parsing via Multi-Task Learning of Structured Embeddings. CoRR abs/1107.3663 (2011)

Yanjun Qi, Oznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman, Jason Weston: Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins. Bioinformatics 26(18) (2010)

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger: Learning to rank with (a lot of) word features. Inf. Retr. 13(3): 291-314 (2010)

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri: Half Transductive Ranking. Journal of Machine Learning Research - Proceedings Track 9: 49-56 (2010)

Antoine Bordes, Nicolas Usunier, Ronan Collobert, Jason Weston: Towards Understanding Situated Natural Language. Journal of Machine Learning Research - Proceedings Track 9: 65-72 (2010)

Jason Weston, Samy Bengio, Nicolas Usunier: Large scale image annotation: learning to rank with joint word-image embeddings. Machine Learning 81(1): 21-35 (2010)

Frédéric Ratle, Gustavo Camps-Valls, Jason Weston: Semisupervised Neural Networks for Efficient Hyperspectral Image Classification. IEEE T. Geoscience and Remote Sensing 48(5): 2271-2282 (2010)

Antoine Bordes, Nicolas Usunier, Jason Weston: Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences. ICML 2010: 103-110

Samy Bengio, Jason Weston, David Grangier: Label Embedding Trees for Large Multi-Class Tasks. NIPS 2010: 163-171

Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning: Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. ECML/PKDD (2) 2010: 128-144

Iain Melvin, Jason Weston, Christina S. Leslie, William Stafford Noble: RANKPROP: a web server for protein remote homology detection. Bioinformatics 25(1): 121-122 (2009)

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger: Supervised semantic indexing. CIKM 2009: 187-196

Yanjun Qi, Ronan Collobert, Pavel P. Kuksa, Koray Kavukcuoglu, Jason Weston: Combining labeled and unlabeled data with word-class distribution learning. CIKM 2009: 1737-1740

Bing Bai, Jason Weston, Ronan Collobert, David Grangier: Supervised Semantic Indexing. ECIR 2009: 761-765

Yanjun Qi, Pavel P. Kuksa, Ronan Collobert, Kunihiko Sadamasa, Koray Kavukcuoglu, Jason Weston: Semi-Supervised Sequence Labeling with Self-Learned Features. ICDM 2009: 428-437

Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston: Curriculum learning. ICML 2009: 6

Hossein Mobahi, Ronan Collobert, Jason Weston: Deep learning from temporal coherence in video. ICML 2009: 93

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri: Polynomial Semantic Indexing. NIPS 2009: 64-72

Iain Melvin, Jason Weston, Christina S. Leslie, William Stafford Noble: Combining classifiers for improved classification of proteins from sequence or structure. BMC Bioinformatics 9 (2008)

Ronan Collobert, Jason Weston: A unified architecture for natural language processing: deep neural networks with multitask learning. ICML 2008: 160-167

Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert: Large scale manifold transduction. ICML 2008: 448-455

Jason Weston, Frédéric Ratle, Ronan Collobert: Deep learning via semi-supervised embedding. ICML 2008: 1168-1175

Frédéric Ratle, Jason Weston, Matthew L. Miller: Large-Scale Clustering through Functional Embedding. ECML/PKDD (2) 2008: 266-281

Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie: SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition. BMC Bioinformatics 8(S-4) (2007)

Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie: Multi-class Protein Classification Using Adaptive Codes. Journal of Machine Learning Research 8: 1557-1581 (2007)

Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson: The Need for Open Source Software in Machine Learning. Journal of Machine Learning Research 8: 2443-2466 (2007)

Ronan Collobert, Jason Weston: Fast Semantic Extraction Using a Novel Neural Network Architecture. ACL 2007

Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston: Solving multiclass support vector machines with LaRank. ICML 2007: 89-96

Jason Weston, Rui Kuang, Christina S. Leslie, William Stafford Noble: Protein Ranking by Semi-Supervised Network Propagation. BMC Bioinformatics 7(S-1) (2006)

Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou: Large Scale Transductive SVMs. Journal of Machine Learning Research 7: 1687-1712 (2006)

Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou: Trading convexity for scalability. ICML 2006: 201-208

Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik: Inference with the Universum. ICML 2006: 1009-1016

Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised protein classification using cluster kernels. Bioinformatics 21(15): 3241-3247 (2005)

Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie: Motif-based protein ranking by network propagation. Bioinformatics 21(19): 3711-3718 (2005)

Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou: Fast Kernel Classifiers with Online and Active Learning. Journal of Machine Learning Research 6: 1579-1619 (2005)

Corinna Cortes, Mehryar Mohri, Jason Weston: A general regression technique for learning transductions. ICML 2005: 153-160

Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie: Multi-class protein fold recognition using adaptive codes. ICML 2005: 329-336

Jason Weston, Bernhard Schölkopf, Olivier Bousquet: Joint Kernel Maps. IWANN 2005: 176-191

Christina S. Leslie, Eleazar Eskin, Adiel Cohen, Jason Weston, William Stafford Noble: Mismatch string kernels for discriminative protein classification. Bioinformatics 20(4): 467-476 (2004)

Thomas Navin Lal, Michael Schröder, Thilo Hinterberger, Jason Weston, Martin Bogdan, Niels Birbaumer, Bernhard Schölkopf: Support vector channel selection in BCI. IEEE Trans. Biomed. Engineering 51(6): 1003-1010 (2004)

Gökhan H. Bakir, Léon Bottou, Jason Weston: Breaking SVM Complexity with Cross-Training. NIPS 2004

Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics 19(6): 764-771 (2003)

Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping: Use of the Zero-Norm with Linear Models and Kernel Methods. Journal of Machine Learning Research 3: 1439-1461 (2003)

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Trans. Pattern Anal. Mach. Intell. 25(5): 623-633 (2003)

Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf: Learning to Find Pre-Images. NIPS 2003

Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos K. Logothetis, Bernhard Schölkopf: Prediction on Spike Data Using Kernel Algorithms. NIPS 2003

Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised Protein Classification Using Cluster Kernels. NIPS 2003

Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf: Learning with Local and Global Consistency. NIPS 2003

Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf: Ranking on Data Manifolds. NIPS 2003

Paul Pavlidis, Jason Weston, Jinsong Cai, William Stafford Noble: Learning Gene Functional Classifications from Multiple Data Types. Journal of Computational Biology 9(2): 401-411 (2002)

Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik: Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 46(1-3): 389-422 (2002)

Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from almost Orthogonal Patterns. ECML 2002: 511-528

Olivier Chapelle, Jason Weston, Bernhard Schölkopf: Cluster Kernels for Semi-Supervised Learning. NIPS 2002: 585-592

Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880

Christina S. Leslie, Eleazar Eskin, Jason Weston, William Stafford Noble: Mismatch String Kernels for SVM Protein Classification. NIPS 2002: 1417-1424

Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from Almost Orthogonal Patterns. PKDD 2002: 494-511

André Elisseeff, Jason Weston: A kernel method for multi-labelled classification. NIPS 2001: 681-687

Paul Pavlidis, Jason Weston, Jinsong Cai, William Noble Grundy: Gene functional classification from heterogeneous data. RECOMB 2001: 249-255

Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik: Vicinal Risk Minimization. NIPS 2000: 416-422

Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik: Feature Selection for SVMs. NIPS 2000: 668-674

Jason Weston, Chris Watkins: Support vector machines for multi-class pattern recognition. ESANN 1999: 219-224

Jason Weston: Leave-One-Out Support Vector Machines. IJCAI 1999: 727-733

Olivier Chapelle, Vladimir Vapnik, Jason Weston: Transductive Inference for Estimating Values of Functions. NIPS 1999: 421-427

Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Invariant Feature Extraction and Classification in Kernel Spaces. NIPS 1999: 526-532