Publications

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Books:

Ingemar J. Cox and Matt L. Miller and Jeffrey Bloom and Jessica Fridrich and Ton Kalker: Digital watermarking and steganography (second edition). Morgan Kaufmann (2007)

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

Vapnik, Vladimir: Estimation of Dependences Based on Empirical Data. Springer Verlag (2006)

Lawrence Saul and Yair Weiss and Léon Bottou (editors) : Advances in Neural Information Processing Systems 17. MIT Press (2005) (link)

Ingemar J. Cox and Matt L. Miller and Jeffrey Bloom: Digital watermarking. Morgan Kaufmann (2002)

Articles and Conference Papers:

Eric Cosatto and Christopher Malon and Pierre-Francois Laquerre and Hans-Peter Graf and Akira Saito and Tomoharu Kiyuna and Atsushi Marugame and Ken'ichi Kamijo: Automated gastric cancer diagnosis on H&E-stained sections; large scale training with multiple instance machine learning. SPIE Medical Imaging: Digital Pathology (2013) (link)

Pavel P. Kuksa and Vladimir Pavlovic: Efficient evaluation of large sequence kernels. KDD (2012) (link)

Pavel P. Kuksa: 2D similarity kernels for biological sequence classification. BIOKDD (2012)

M. Gerstein* and et al.* and R. Min* and et al. and M. Snyder (* Co-first authors): Architecture of the human regulatory network derived from ENCODE data. Nature (2012) (link)

C. Malon and E. Brachtel and E. Cosatto and H. P. Graf and A. Kurata and M. Kuroda and J. S. Meyer and A. Saito and S. Wu and Y. Yagi: Mitotic figure recognition: Agreement among pathologists and computerized detector. Analytical Cellular Pathology 35(2) (2012) (link) (preprint)

Pavel P. Kuksa and Imdadullah Khan and Vladimir Pavlovic: Generalized Similarity Kernels for Efficient Sequence Classification. SDM (2012)

Pavel P. Kuksa: Using string kernels to predict gene expression. Snowbird Learning Workshop (2012) (link)

Pavel P. Kuksa: 2D similarity kernels and representations for sequence data. Snowbird Learning Workshop (2012) (link)

Pavel P. Kuksa: Efficient sequence kernel-based genome-wide prediction of transcription factors. ICPR (2012)

Pavel P. Kuksa: Efficient time series classification with Multivariate similarity kernels. NYAS Machine Learning Symposium (2012) (link)

Yanjun Qi and Pierre-Francois Laquerre: Retrieving Medical Records with sennamed: NEC Labs America at TREC 2012 Medical Record Track. Proceedings of the 2012 Text Retrieval Conference (2012)

C. Cheng and R. Alexander and R. Min and et al. and E. Birney and Z. Weng and M. Gerstein: Understanding transcriptional regulation by integrative analysis of transcription factor binding data. Genome Research (2012) (link)

The ENCODE Project Consortium including R. Min: An integrated encyclopedia of DNA elements in the human genome. Nature (2012) (link)

Dmitriy Bespalov and Yanjun Qi and Bing Bai and Ali Shokoufandeh: Large-scale Image Classification Using Supervised Spatial Encoder. ICPR (2012) (link)

Siddharth Gopal and Yiming Yang and Bing Bai and Alexandru Niculescu-Mizil: Bayesian Models for Large-scale Hierarchical Classification. NIPS (2012) (link)

Abhishek Kumar and Alexandru Niculescu-Mizil and Koray Kavukcuoglu and Hal Daume III: A Binary Classification Framework for Two Stage Multiple Kernel Learning. Proceedings of the International Conference on Machine Learning (2012)

C. Malon and B. Bai and K. S. Hasan: Slot-Filling by Substring Extraction at TAC KBP 2012 (Team Papelo). NIST Text Analysis Conference (TAC) 2012 Proceedings (2012) (preprint)

Dmitriy Bespalov and Yanjun Qi and Bing Bai and Ali Shokoufandeh: Sentiment Classification with Supervised Sequence Encoder. ECML PKDD (2012) (link)

Clement Farabet and Yann LeCun and Koray Kavukcuoglu and Berin Martini and Polina Akselrod and Selcuk Talay and Eugenio Culurciello: Large-scale FPGA-based convolutional networks. Scaling Up Machine Learning Ron Bekkerman and Mikhail Bilenko and John Langford (editors) (2011)

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

Xi Chen and Yanjun Qi and Bing Bai and Qihang Lin and Jaime Carbonell : Sparse Latent Semantic Analysis. SIAM 2011 International Conference on Data Mining (2011) (link)

A. Majumdar and S. Cadambi and S.T. Chakradhar and H.P. Graf: A Parallel Accelerator for Semantic Search. Proc. IEEE Symp. Application Specific Processes, SASP 2011 (2011)

Xia Ning and Yanjun Qi: Semi-Supervised Convolution Graph Kernels for Relation Extraction. SIAM 2011 International Conference on Data Mining (2011) (link)

M. Ogura and A. Saito and H.P. Graf and E. Cosatto and C. Malon and A. Marugame and T. Kiyuna and Y. Yamashita and M. Fukumoto: The e-Pathologist Cancer Diagnosis Assistance System for Gastric Biopsy Tissues (Abstract). Analytical Cellular Pathology 34(4) (2011) (link)

C. Malon and E. Cosatto: Dynamic radial contour extraction by splitting homogeneous areas. Computer Analysis of Image and Patterns (6854) (2011) (link)

Pavel P. Kuksa and Vladimir Pavlovic: Efficient Evaluation of Large Sequence Kernels. NYAS Machine Learning Symposium (2011) (link)

I. Durdanovic and E. Cosatto and H.P. Graf and S. Cadambi and V. Jakkula and S. Chakradhar and A. Majumdar: Massive SVM Parallelization using Hardware Accelerators. Scaling up Machine Learning R. Bekkerman and M. Bilenko and J. Langford (editors) (2011)

Ronan Collobert and Jason Weston and Léon Bottou and Michael Karlen and Koray Kavukcuoglu and Pavel Kuksa: Natural Language Processing (almost) from Scratch. Journal of Machine Learning (12) (2011)

P. Kuksa and Y. Qi: Semi-Supervised Bio-Named Entity Recognition with Word-Codebook Learning. SIAM International Conference on Data Mining (SDM) (2010)

S.Cadambi and A. Majumdar and M. Becchi and S.T. Chakradhar and H.P. Graf: A Programmable Parallel Accelerator for Learning and Classification. Proc. Int. Conf. Parallel Architectures and Compilatio (2010)

D. Grangier and I. Melvin: Feature Set Embedding for Incomplete Data. Advances in Neural Information Processing Systems (NIPS) (2010) (link)

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

Xi Chen and Bing Bai and Yanjun Qi and Qihang Lin and Jaime Carbonell: Learning Preferences with Millions of Parameters by Enforcing Sparsity. International Conference on Data Mining (2010)

Y. Qi and O.Tastan and J. Carbonell and J. Klein-Seetharaman and J. Weston: Semi-Supervised Multi-Task Learning for Predicting Interactions between HIV-1 and Human Proteins. European Conference on Computational Biology (ECCB) (2010)

P. Kuksa and Y. Qi and B. Bai and R. Collobert and J.Weston and V. Pavlovic and X. Ning: Semi-Supervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction. ECML PKDD 2010 ( European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases ) (2010)

Xi Chen and Yanjun Qi and Bing Bai and Qihang Lin and Jaime Carbonell: Sparse Latent Semantic Analysis. NIPS Workshop on Practical Application of Sparse Modeling: Open Issues and New Directions (2010)

O. Tastan and Y. Qi and J.G. Carbonell and J. Klein-Seetharaman: Prediction of Interactions between HIV-1 and Human Proteins by Information Integration. Pacific Symposium on Biocomputing (PSB) 14 (2009)

Meyer, John and Cosatto, Eric and Graf, Hans Peter: Mitotic Index of Invasive Breast Carcinoma. Archives of Pathology and Laboratory Medicine 133(11) (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)

Y. Qi and P. Kuksa and R. Collobert and K. Sadamasa and K. Kavukcuoglu and J.Weston: Semi-Supervised Sequence Labeling with Self-Learned Feature. IEEE International Conference on Data Mining (ICDM) (2009)

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 Y. Bengio and D. Schuurmans and J. Lafferty and C. K. I. Williams and A. Culotta (editors) (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 (a lot of) Word Features. Information Retrieval Special Issue: Learning to Rank for IR (2009) (link)

Y. Qi and R. Collobert and P. Kuksa and K. Kavukcuoglu and J.Weston: Combining Labeled and Unlabeled Data for Word-Class Distribution Learning. The 18th ACM Conference on Information and Knowledge Management (CIKM) (2009)

Y. Qi and HK. Dhiman and et al and Z. Bar-Joseph and J. Klein-Seetharaman: Systematic prediction of human membrane receptor interactions. PROTEOMICS (9) (2009)

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)

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)

Sankaradass, Murugan and Jakkula, Venkata and Cadambi, Srihari and Durdanovic, Igor and Cosatto, Eric and Chakradhar, Srimat and Graf, Hans Peter: A Massively Parallel Coprocessor for Convolutional Neural Networks. Proc. Application-specific Systems, Architectures and Processors, ASAP 2009 (2009)

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 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)

Kuksa, Pavel and Huang, Pai-Hsi and Pavlovic, Vladimir: Efficient use of unlabeled data for protein sequence classification: a comparative study. BMC Bioinformatics 11(Suppl 4) (2009) (link)

Cadambi, Srihari and Durdanovic, Igor and Jakkula, Venkata and Sankaradass, Murugan and Cosatto, Eric and Chakradhar, Srimat and Graf, Hans Peter: A Massively Parallel FPGA Based Co-Processor for Support Vector Machines. Proc. Field Programmable Custom Computing Machines, FCCM (2009)

Meyer, John and Cosatto, Eric and Graf, Hans Peter: Mitotic Index of Breast Carcinoma: Understanding and Remedying Irreproducibility. US and Canadian Academy of Pathology, 2009 Annual Meeting (2009)

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

Léon Bottou and Olivier Bousquet: The Tradeoffs of Large Scale Learning. Advances in Neural Information Processing Systems J.C. Platt and D. Koller and Y. Singer and S. Roweis (editors) () (2008) (link)

R. El-Yaniv and D. Pechyony and V. Vapnik: Large margin vs. large volume in transductive learning. Machine Learning Journal 72(3) (2008)

Graf, Hans Peter and Cadambi, Srihari and Durdanovic, Igor and Jakkula, Venkata and Sankardadass, Murugan and Cosatto, Eric and Chakradhar, Srimat: A Massively Parallel Digital Learning Processor. Advances in Neural Information Processing Systems (21) (2008)

Léon Bottou and Olivier Bousquet: Learning Using Large Datasets. Mining Massive DataSets for Security (2008) (link)

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

C. Malon and M. Miller and C. Burger and E. Cosatto and H.P. Graf: Identifying Histological Elements with Convolutional Neural Networks. Proc. ACM CSTST 2008 Workshop on Computational Intelligence in Medical Imaging (2008) (link) (preprint)

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)

Cosatto, Eric and Miller, Matt and Graf, Hans Peter and Meyer, John: Grading Nuclear Pleomorphism on Histological Micrographs. Proc. Int. Conf. Pattern Recognition (2008)

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)

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)

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)

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)

Antoine Bordes and Nicolas Usunier and Léon Bottou: Sequence Labelling SVMs Trained in One Pass. Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008 Daelemans, Walter and Goethals, Bart and Morik, Katharina (editors) (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 (8) (2007) (link)

Akshay Vashist and Casimir A. Kulikowski and Ilya B. Muchnik: Ortholog Clustering on a Multipartite Graph. IEEE/ACM Trans. Comput. Biology Bioinform. 4(1) (2007)

Seyda Ertekin and Jian Huang and Léon Bottou and C. Lee Giles: Learning on the Border: Active Learning in Imbalanced Data Classification. Proceedings of the 16th Conference on Information and Knowledge Management, CIKM2007 (2007) (link)

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

Durdanovic, I. and Cosatto, E. and Graf, H.P.: Large Scale Parallel SVM Implementation. Large Scale Kernel Machines Bottou, L. and Chapelle, O. and DeCoste, D. and Weston, J. (editors) (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)

Bottou, Léon and Lin, Chih-Jen: Support Vector Machine Solvers. Large Scale Kernel Machines Bottou, Léon and Chapelle, Olivier and DeCost (editors) (2007) (link)

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

Loosli, Gaëlle and Canu, Stéphane and Bottou, Léon: Training Invariant Support Vector Machines using Selective Sampling. Large Scale Kernel Machines Bottou, Léon and Chapelle, Olivier and DeCost (editors) (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 (8) (2007)

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)

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)

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 Zoubin Ghahramani (editor) (2007) (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)

Lal, T. N. and Chapelle, Olivier and Weston, Jason and Elisseeff, Andre: Embedded Methods. Feature extraction, foundations and Applications I. Guyon and S. Gunn and M. Nikravesh and L. Zadeh (editors) (2006) (link)

Vapnik, Vladimir: Transductive Inference and Semi-Supervised Learning. Semi-Supervised Learning (2006)

Collobert, Ronan and Sinz, Fabian and Weston, Jason and Bottou, Léon: Large Scale Transductive SVMs. Journal of Machine Learning Research (7) (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)

LeCun, Y. and Muller, U. and Ben, J. and Cosatto, E. and Flepp, B.: Off-road obstacle avoidance through end-to-end learning. Advances in neural information processing systems (18) (2006)

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)

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)

Graf, Hans Peter and Cosatto, Eric and Bottou, Léon and Durdanovic, Igor and Vapnik, Vladimir: Parallel Support Vector Machines: The Cascade SVM. Advances in Neural Information Processing Systems Saul, Lawrence and Weiss, Yair and Bottou, Léon (editors) (17) (2005) (link)

Bordes, Antoine and Bottou, Léon: The Huller: a simple and efficient online SVM. Machine Learning: ECML 2005 (2005) (link)

BakIr, Gökhan and Bottou, Léon and Weston, Jason: Breaking SVM Complexity with Cross-Training. Advances in Neural Information Processing Systems Saul, Lawrence and Weiss, Yair and Bottou, Léon (editors) (17) (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)

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 Cowell, Robert G. and Ghahramani, Zoubin (editors) (2005) (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) Cabestany, J., A. Prieto, F. Sandoval (editor) (LNCS 3512) (2005) (link)

Ning, Feng and Delhomme, Damien and LeCun, Yann and Piano, Fabio and Bottou, Léon and Barbano, Paolo Emilio: Toward Automatic Phenotyping of Developing Embryos from Videos. IEEE Transactions in Image Processing 14(9) (2005) (link)

Kuang, Rui and Weston, Jason and Noble, William Stafford and Leslie, Christina: Motif-based protein ranking by network propagation. Bioinformatics 21(19) (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 21(15) (2005) (link)

Noble, William Stafford and Kuang, Rui and Leslie, Christina and Weston, Jason: Identifying remote protein homologs by network propagation. FEBS Journal (272) (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)

Bi, J. and Vapnik, Vladimir: Learning with rigorous support vector machines. Proceedings of the 16th Annual Conference on Learning Theory

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

Bottou, Léon and LeCun, Yann: On-line Learning for Very Large Datasets. Applied Stochastic Models in Business and Industry 21(2) (2005) (link)

Bottou, Léon and LeCun, Yann: Graph Transformer Networks for Image Recognition. Bulletin of the International Statistical Institute (ISI) (2005) (link)

Osadchy, M. and Miller, Matthew and LeCun, Y.: Synergistic Face Detection and Pose Estimation with Energy-Based Models. Advances in Neural Information Processing Systems (NIPS 2004) (2004)

Bottou, Léon and LeCun, Yann: Large Scale Online Learning. Advances in Neural Information Processing Systems 16 Thrun, Sebastian and Saul, Lawrence and Bernhard Schölkopf (editors) (2004) (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 101(17) (2004) (link)

LeCun, Yann and Bottou, Léon and HuangFu, Jie: Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. Proc. of Computer Vision and Pattern Recognition (2004) (link)

Weston, Jason and Chapelle, Olivier and Elisseeff, Andre and Schölkopf, Bernhard and Vapnik, Vladimir: Kernel Dependency Estimation.. Advances in Neural Information Processing Systems Becker, S., S. Thrun, K. Obermayer (editor) (15) (2003) (link)

Antoine Bordes and Léon Botto: Solving MultiClass Support Vector Machines with LaRank. Proceedings of the 24th International Machine Learning Conference Zoubin Ghahramani (editor) (00)

Tech Reports:

S. Chowdhury and Y. Qi and A. Stewart and R. Ostroff and R. Min*: Cancer Diagnosis with QUIRE: QUadratic Interactions among infoRmative fEatures. NEC Labs America, TR/TN # 2012-TR115 (2012) (link)

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)

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)

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Click here to see a list of publications from all staff and alumni.