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Jason Weston: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
    A Kernel Approach for Learning from almost Orthogonal Patterns. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:511-528 [Conf]
  2. Jason Weston, Chris Watkins
    Support vector machines for multi-class pattern recognition. [Citation Graph (0, 0)][DBLP]
    ESANN, 1999, pp:219-224 [Conf]
  3. Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
    Trading convexity for scalability. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:201-208 [Conf]
  4. Corinna Cortes, Mehryar Mohri, Jason Weston
    A general regression technique for learning transductions. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:153-160 [Conf]
  5. Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie
    Multi-class protein fold recognition using adaptive codes. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:329-336 [Conf]
  6. Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik
    Inference with the Universum. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1009-1016 [Conf]
  7. Jason Weston
    Leave-One-Out Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:727-733 [Conf]
  8. Jason Weston, Bernhard Schölkopf, Olivier Bousquet
    Joint Kernel Maps. [Citation Graph (0, 0)][DBLP]
    IWANN, 2005, pp:176-191 [Conf]
  9. Gökhan H. Bakir, Léon Bottou, Jason Weston
    Breaking SVM Complexity with Cross-Training. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  10. Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf
    Learning to Find Pre-Images. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  11. Olivier Chapelle, Vladimir Vapnik, Jason Weston
    Transductive Inference for Estimating Values of Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:421-427 [Conf]
  12. Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik
    Vicinal Risk Minimization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:416-422 [Conf]
  13. Olivier Chapelle, Jason Weston, Bernhard Schölkopf
    Cluster Kernels for Semi-Supervised Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:585-592 [Conf]
  14. Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf
    Prediction on Spike Data Using Kernel Algorithms. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  15. André Elisseeff, Jason Weston
    A kernel method for multi-labelled classification. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:681-687 [Conf]
  16. Christina S. Leslie, Eleazar Eskin, Jason Weston, William Stafford Noble
    Mismatch String Kernels for SVM Protein Classification. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1417-1424 [Conf]
  17. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
    Invariant Feature Extraction and Classification in Kernel Spaces. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:526-532 [Conf]
  18. Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik
    Kernel Dependency Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:873-880 [Conf]
  19. Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble
    Semi-supervised Protein Classification Using Cluster Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  20. Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik
    Feature Selection for SVMs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:668-674 [Conf]
  21. Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
    Learning with Local and Global Consistency. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  22. Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
    Ranking on Data Manifolds. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  23. Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
    A Kernel Approach for Learning from Almost Orthogonal Patterns. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:494-511 [Conf]
  24. Paul Pavlidis, Jason Weston, Jinsong Cai, William Noble Grundy
    Gene functional classification from heterogeneous data. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2001, pp:249-255 [Conf]
  25. Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie
    Motif-based protein ranking by network propagation. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:19, pp:3711-3718 [Journal]
  26. Christina S. Leslie, Eleazar Eskin, Adiel Cohen, Jason Weston, William Stafford Noble
    Mismatch string kernels for discriminative protein classification. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:4, pp:- [Journal]
  27. Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble
    Semi-supervised protein classification using cluster kernels. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:15, pp:3241-3247 [Journal]
  28. 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. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2003, v:19, n:6, pp:764-771 [Journal]
  29. Paul Pavlidis, Jason Weston, Jinsong Cai, William Stafford Noble
    Learning Gene Functional Classifications from Multiple Data Types. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:9, n:2, pp:401-411 [Journal]
  30. Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping
    Use of the Zero-Norm with Linear Models and Kernel Methods. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:3, n:, pp:1439-1461 [Journal]
  31. Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou
    Fast Kernel Classifiers with Online and Active Learning. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1579-1619 [Journal]
  32. Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou
    Large Scale Transductive SVMs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1687-1712 [Journal]
  33. Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik
    Gene Selection for Cancer Classification using Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:389-422 [Journal]
  34. 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. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:5, pp:623-633 [Journal]
  35. Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston
    Solving multiclass support vector machines with LaRank. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:89-96 [Conf]

  36. Fast Semantic Extraction Using a Novel Neural Network Architecture. [Citation Graph (, )][DBLP]


  37. Supervised semantic indexing. [Citation Graph (, )][DBLP]


  38. Combining labeled and unlabeled data with word-class distribution learning. [Citation Graph (, )][DBLP]


  39. Supervised Semantic Indexing. [Citation Graph (, )][DBLP]


  40. Semi-Supervised Sequence Labeling with Self-Learned Features. [Citation Graph (, )][DBLP]


  41. Deep learning via semi-supervised embedding. [Citation Graph (, )][DBLP]


  42. Large scale manifold transduction. [Citation Graph (, )][DBLP]


  43. A unified architecture for natural language processing: deep neural networks with multitask learning. [Citation Graph (, )][DBLP]


  44. Curriculum learning. [Citation Graph (, )][DBLP]


  45. Deep learning from temporal coherence in video. [Citation Graph (, )][DBLP]


  46. Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences. [Citation Graph (, )][DBLP]


  47. Large-Scale Clustering through Functional Embedding. [Citation Graph (, )][DBLP]


  48. Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. [Citation Graph (, )][DBLP]


  49. RANKPROP: a web server for protein remote homology detection. [Citation Graph (, )][DBLP]


  50. Combining classifiers for improved classification of proteins from sequence or structure. [Citation Graph (, )][DBLP]


  51. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition. [Citation Graph (, )][DBLP]


  52. Protein Ranking by Semi-Supervised Network Propagation. [Citation Graph (, )][DBLP]


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