The SCEAS System
Navigation Menu
Introduction
Collection Based
Clustering
Ranking
Paper Based
Journals
Conferences
DB Status
Statistics
Search

Search the dblp DataBase

Title:
Author:
John Shawe-Taylor: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jong Yong Kim, John Shawe-Taylor
    An Approximate String-Matching Algorithm. [Citation Graph (1, 0)][DBLP]
    Theor. Comput. Sci., 1992, v:92, n:1, pp:107-117 [Journal]
  2. David R. Hardoon, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
    A Correlation Approach for Automatic Image Annotation. [Citation Graph (0, 0)][DBLP]
    ADMA, 2006, pp:681-692 [Conf]
  3. Amiran Ambroladze, John Shawe-Taylor
    Complexity of Pattern Classes and Lipschitz Property. [Citation Graph (0, 0)][DBLP]
    ALT, 2004, pp:181-193 [Conf]
  4. Carlos Domingo, John Shawe-Taylor
    The Complexity of Learning Minor Closed Graph Classes. [Citation Graph (0, 0)][DBLP]
    ALT, 1995, pp:249-260 [Conf]
  5. Matthew Henderson, John Shawe-Taylor, Janez Zerovnik
    Mixture of Vector Experts. [Citation Graph (0, 0)][DBLP]
    ALT, 2005, pp:386-398 [Conf]
  6. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    ALT, 2002, pp:23-40 [Conf]
  7. Amiran Ambroladze, John Shawe-Taylor
    When Is Small Beautiful? [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:729-730 [Conf]
  8. Martin Anthony, Graham Brightwell, David A. Cohen, John Shawe-Taylor
    On Exact Specification by Examples. [Citation Graph (0, 0)][DBLP]
    COLT, 1992, pp:311-318 [Conf]
  9. Martin Anthony, Norman Biggs, John Shawe-Taylor
    The Learnability of Formal Concepts. [Citation Graph (0, 0)][DBLP]
    COLT, 1990, pp:246-257 [Conf]
  10. Thore Graepel, Ralf Herbrich, John Shawe-Taylor
    Generalisation Error Bounds for Sparse Linear Classifiers. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:298-303 [Conf]
  11. Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson
    Covering Numbers for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    COLT, 1999, pp:267-277 [Conf]
  12. Ralf Herbrich, Thore Graepel, John Shawe-Taylor
    Sparsity vs. Large Margins for Linear Classifiers. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:304-308 [Conf]
  13. Jaz S. Kandola, Thore Graepel, John Shawe-Taylor
    Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:288-302 [Conf]
  14. John Shawe-Taylor
    Sample Sizes for Sigmoidal Neural Networks. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:258-264 [Conf]
  15. John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony
    A Framework for Structural Risk Minimisation. [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:68-76 [Conf]
  16. John Shawe-Taylor, Nello Cristianini
    Further Results on the Margin Distribution. [Citation Graph (0, 0)][DBLP]
    COLT, 1999, pp:278-285 [Conf]
  17. John Shawe-Taylor, Robert C. Williamson
    A PAC Analysis of a Bayesian Estimator. [Citation Graph (0, 0)][DBLP]
    COLT, 1997, pp:2-9 [Conf]
  18. Jong Yong Kim, John Shawe-Taylor
    Fast Multiple Keyword Searching. [Citation Graph (0, 0)][DBLP]
    CPM, 1992, pp:41-51 [Conf]
  19. Jonathan Baxter, John Shawe-Taylor
    Learning to Compress Ergodic Sources. [Citation Graph (0, 0)][DBLP]
    Data Compression Conference, 1996, pp:423- [Conf]
  20. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2002, pp:12- [Conf]
  21. Hongying Meng, John Shawe-Taylor, Sándor Szedmák, Jason D. R. Farquhar
    Support Vector Machine to Synthesise Kernels. [Citation Graph (0, 0)][DBLP]
    Deterministic and Statistical Methods in Machine Learning, 2004, pp:242-255 [Conf]
  22. Alexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington
    The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:630-637 [Conf]
  23. Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer
    Using String Kernels to Identify Famous Performers from Their Playing Style. [Citation Graph (0, 0)][DBLP]
    ECML, 2004, pp:384-395 [Conf]
  24. Petroula Tsampouka, John Shawe-Taylor
    Analysis of Generic Perceptron-Like Large Margin Classifiers. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:750-758 [Conf]
  25. Petroula Tsampouka, John Shawe-Taylor
    Constant Rate Approximate Maximum Margin Algorithms. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:437-448 [Conf]
  26. Nello Cristianini, Colin Campbell, John Shawe-Taylor
    A multiplicative updating algorithm for training support vector machine. [Citation Graph (0, 0)][DBLP]
    ESANN, 1999, pp:189-194 [Conf]
  27. Sándor Szedmák, John Shawe-Taylor
    Synthesis of maximum margin and multiview learning using unlabeled data. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:479-484 [Conf]
  28. John Shawe-Taylor
    Confidence Estimates of Classification Accuracy on New Examples. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1997, pp:260-271 [Conf]
  29. John Shawe-Taylor, Nello Cristianini
    Margin Distribution Bounds on Generalization. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:263-273 [Conf]
  30. John Shawe-Taylor, Nello Cristianini
    Generalization Performance of Classifiers in Terms of Observed Covering Numbers. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:274-284 [Conf]
  31. Barry Rising, Max van Daalen, Peter Burge, John Shawe-Taylor
    Parallel Graph colouring using FPGAs. [Citation Graph (0, 0)][DBLP]
    FPL, 1997, pp:121-130 [Conf]
  32. Patrick W. Fowler, Tomaz Pisanski, John Shawe-Taylor
    Molecular Graph Eigenvectors for Molecular Coordinates. [Citation Graph (0, 0)][DBLP]
    Graph Drawing, 1994, pp:282-285 [Conf]
  33. Kristin P. Bennett, Ayhan Demiriz, John Shawe-Taylor
    A Column Generation Algorithm For Boosting. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:65-72 [Conf]
  34. Nello Cristianini, John Shawe-Taylor, Huma Lodhi
    Latent Semantic Kernels. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:66-73 [Conf]
  35. Nello Cristianini, John Shawe-Taylor, Peter Sykacek
    Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:109-117 [Conf]
  36. Thorsten Joachims, Nello Cristianini, John Shawe-Taylor
    Composite Kernels for Hypertext Categorisation. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:250-257 [Conf]
  37. Alain Lehmann, John Shawe-Taylor
    A probabilistic model for text kernels. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:537-544 [Conf]
  38. Jure Leskovec, John Shawe-Taylor
    Linear Programming Boosting for Uneven Datasets. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:456-463 [Conf]
  39. Yaoyong Li, Hugo Zaragoza, Ralf Herbrich, John Shawe-Taylor, Jaz S. Kandola
    The Perceptron Algorithm with Uneven Margins. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:379-386 [Conf]
  40. Mario Marchand, John Shawe-Taylor
    Learning with the Set Covering Machine. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:345-352 [Conf]
  41. Mario Marchand, Mohak Shah, John Shawe-Taylor, Marina Sokolova
    The Set Covering Machine with Data-Dependent Half-Spaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:520-527 [Conf]
  42. Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
    Learning hierarchical multi-category text classification models. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:744-751 [Conf]
  43. Matthias Rychetsky, John Shawe-Taylor, Manfred Glesner
    Direct Bayes Point Machines. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:815-822 [Conf]
  44. Craig Saunders, Hauke Tschach, John Shawe-Taylor
    Syllables and other String Kernel Extensions. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:530-537 [Conf]
  45. Donghui Wu, Kristin P. Bennett, Nello Cristianini, John Shawe-Taylor
    Large Margin Trees for Induction and Transduction. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:474-483 [Conf]
  46. Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Taylor
    Boosting the Margin Distribution. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2000, pp:54-59 [Conf]
  47. Anders Meng, John Shawe-Taylor
    An Investigation of Feature Models for Music Genre Classification Using the Support Vector Classifier. [Citation Graph (0, 0)][DBLP]
    ISMIR, 2005, pp:604-609 [Conf]
  48. Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc J. Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang
    The 2005 PASCAL Visual Object Classes Challenge. [Citation Graph (0, 0)][DBLP]
    MLCW, 2005, pp:117-176 [Conf]
  49. Barry Rising, Max van Daalen, John Shawe-Taylor, Peter Burge, Janez Zerovnik
    A Neural Accelerator for Graph Colouring Based on an Edge Adding Technique. [Citation Graph (0, 0)][DBLP]
    NC, 1998, pp:652-656 [Conf]
  50. Nello Cristianini, Colin Campbell, John Shawe-Taylor
    Dynamically Adapting Kernels in Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:204-210 [Conf]
  51. Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola
    On Kernel-Target Alignment. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:367-373 [Conf]
  52. Nello Cristianini, John Shawe-Taylor, Jaz S. Kandola
    Spectral Kernel Methods for Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:649-655 [Conf]
  53. Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor, Sándor Szedmák
    Two view learning: SVM-2K, Theory and Practice. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  54. Thore Graepel, Ralf Herbrich, Andriy Kharechko, John Shawe-Taylor
    Semi-Definite Programming by Perceptron Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  55. Grigoris J. Karakoulas, John Shawe-Taylor
    Optimizing Classifers for Imbalanced Training Sets. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:253-259 [Conf]
  56. Jaz S. Kandola, John Shawe-Taylor, Nello Cristianini
    Learning Semantic Similarity. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:657-664 [Conf]
  57. John Langford, John Shawe-Taylor
    PAC-Bayes & Margins. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:423-430 [Conf]
  58. Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins
    Text Classification using String Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:563-569 [Conf]
  59. John C. Platt, Nello Cristianini, John Shawe-Taylor
    Large Margin DAGs for Multiclass Classification. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:547-553 [Conf]
  60. Craig Saunders, John Shawe-Taylor, Alexei Vinokourov
    String Kernels, Fisher Kernels and Finite State Automata. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:633-640 [Conf]
  61. Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
    Support Vector Method for Novelty Detection. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:582-588 [Conf]
  62. John Shawe-Taylor
    Threshold Network Learning in the Presence of Equivalences. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:879-886 [Conf]
  63. John Shawe-Taylor, Nello Cristianini
    Data-Dependent Structural Risk Minimization for Perceptron Decision Trees. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  64. John Shawe-Taylor, Nello Cristianini, Jaz S. Kandola
    On the Concentration of Spectral Properties. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:511-517 [Conf]
  65. John Shawe-Taylor, Christopher K. I. Williams
    The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:367-374 [Conf]
  66. John Shawe-Taylor, Jieyu Zhao
    Generalisation of A Class of Continuous Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:267-273 [Conf]
  67. Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
    The Entropy Regularization Information Criterion. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:342-348 [Conf]
  68. Marina Sokolova, Mario Marchand, Nathalie Japkowicz, John Shawe-Taylor
    The Decision List Machine. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:921-928 [Conf]
  69. Alexei Vinokourov, John Shawe-Taylor, Nello Cristianini
    Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1473-1480 [Conf]
  70. Barry Rising, John Shawe-Taylor, Janez Zerovnik
    Graph Colouring by Maximal Evidence Edge Adding. [Citation Graph (0, 0)][DBLP]
    PATAT, 2000, pp:294-308 [Conf]
  71. Shutao Li, John Shawe-Taylor
    Texture Classification by Combining Wavelet and Contourlet Features. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2004, pp:1126-1134 [Conf]
  72. Nicola Cancedda, Cyril Goutte, Jean-Michel Renders, Nicolò Cesa-Bianchi, Alex Conconi, Yaoyong Li, John Shawe-Taylor, Alexei Vinokourov, Thore Graepel, Claudio Gentile
    Kernel Methods for Document Filtering. [Citation Graph (0, 0)][DBLP]
    TREC, 2002, pp:- [Conf]
  73. John Shawe-Taylor
    Neural Network Learning: Theoretical Foundation. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2001, v:22, n:2, pp:99-100 [Journal]
  74. John Shawe-Taylor
    Classification Accuracy Based on Observed Margin. [Citation Graph (0, 0)][DBLP]
    Algorithmica, 1998, v:22, n:1/2, pp:157-172 [Journal]
  75. Martin Anthony, Peter L. Bartlett, Yuval Ishai, John Shawe-Taylor
    Valid Generalisation from Approximate Interpolation. [Citation Graph (0, 0)][DBLP]
    Combinatorics, Probability & Computing, 1996, v:5, n:, pp:191-214 [Journal]
  76. Martin Anthony, John Shawe-Taylor
    Using the Perceptron Algorithm to Find Consistent Hypotheses. [Citation Graph (0, 0)][DBLP]
    Combinatorics, Probability & Computing, 1993, v:2, n:, pp:385-387 [Journal]
  77. John Shawe-Taylor
    Fast String Matching in Stationary Ergodic Sources. [Citation Graph (0, 0)][DBLP]
    Combinatorics, Probability & Computing, 1996, v:5, n:, pp:415-427 [Journal]
  78. Martin Anthony, Graham Brightwell, John Shawe-Taylor
    On Specifying Boolean Functions by Labelled Examples. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1995, v:61, n:1, pp:1-25 [Journal]
  79. Martin Anthony, John Shawe-Taylor
    A Result of Vapnik with Applications. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1993, v:47, n:3, pp:207-217 [Journal]
  80. Martin Anthony, John Shawe-Taylor
    A Result of Vapnik with Applications. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1994, v:52, n:2, pp:211- [Journal]
  81. Martin Anthony, John Shawe-Taylor
    A Sufficient Condition for Polynomial Distribution-dependent Learnability. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1997, v:77, n:1, pp:1-12 [Journal]
  82. John Shawe-Taylor
    Special Issue of DAM on the Vapnik-chervonenkis Dimension. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1998, v:86, n:1, pp:1-2 [Journal]
  83. John Shawe-Taylor, Martin Anthony, Norman Biggs
    Bounding Sample Size with the Vapnik-Chervonenkis Dimension. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1993, v:42, n:1, pp:65-73 [Journal]
  84. Jeffrey Wood, John Shawe-Taylor
    Representation Theory and Invariant Neural Networks. [Citation Graph (0, 0)][DBLP]
    Discrete Applied Mathematics, 1996, v:69, n:1-2, pp:33-60 [Journal]
  85. John Shawe-Taylor
    Sample Sizes for Threshold Networks with Equivalences [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1995, v:118, n:1, pp:65-72 [Journal]
  86. Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Taylor
    Boosting strategy for classification. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2002, v:6, n:2, pp:149-174 [Journal]
  87. Tomaz Pisanski, John Shawe-Taylor
    Characterizing Graph Drawing with Eigenvectors. [Citation Graph (0, 0)][DBLP]
    Journal of Chemical Information and Computer Sciences, 2000, v:40, n:3, pp:567-571 [Journal]
  88. Chris D. Godsil, John Shawe-Taylor
    Distance-regularised graphs are distance-regular or distance-biregular. [Citation Graph (0, 0)][DBLP]
    J. Comb. Theory, Ser. B, 1987, v:43, n:1, pp:14-24 [Journal]
  89. Bojan Mohar, John Shawe-Taylor
    Distance-biregular graphs with 2-valent vertices and distance-regular line graphs. [Citation Graph (0, 0)][DBLP]
    J. Comb. Theory, Ser. B, 1985, v:38, n:3, pp:193-203 [Journal]
  90. Tomaz Pisanski, John Shawe-Taylor, Joze Vrabec
    Edge-colorability of graph bundles. [Citation Graph (0, 0)][DBLP]
    J. Comb. Theory, Ser. B, 1983, v:35, n:1, pp:12-19 [Journal]
  91. Nello Cristianini, John Shawe-Taylor, Huma Lodhi
    Latent Semantic Kernels. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2002, v:18, n:2-3, pp:127-152 [Journal]
  92. Yaoyong Li, John Shawe-Taylor
    Using KCCA for Japanese-English cross-language information retrieval and document classification. [Citation Graph (0, 0)][DBLP]
    J. Intell. Inf. Syst., 2006, v:27, n:2, pp:117-133 [Journal]
  93. Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins
    Text Classification using String Kernels. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:2, n:, pp:419-444 [Journal]
  94. Mario Marchand, John Shawe-Taylor
    The Set Covering Machine. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:723-746 [Journal]
  95. Juho Rousu, John Shawe-Taylor
    Efficient Computation of Gapped Substring Kernels on Large Alphabets. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1323-1344 [Journal]
  96. Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
    Kernel-Based Learning of Hierarchical Multilabel Classification Models. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1601-1626 [Journal]
  97. Peter Burge, John Shawe-Taylor
    An Unsupervised Neural Network Approach to Profiling the Behavior of Mobile Phone Users for Use in Fraud Detection. [Citation Graph (0, 0)][DBLP]
    J. Parallel Distrib. Comput., 2001, v:61, n:7, pp:915-925 [Journal]
  98. Kristin P. Bennett, Nello Cristianini, John Shawe-Taylor, Donghui Wu
    Enlarging the Margins in Perceptron Decision Trees. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2000, v:41, n:3, pp:295-313 [Journal]
  99. Ayhan Demiriz, Kristin P. Bennett, John Shawe-Taylor
    Linear Programming Boosting via Column Generation. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2002, v:46, n:1-3, pp:225-254 [Journal]
  100. Thore Graepel, Ralf Herbrich, John Shawe-Taylor
    PAC-Bayesian Compression Bounds on the Prediction Error of Learning Algorithms for Classification. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2005, v:59, n:1-2, pp:55-76 [Journal]
  101. John Shawe-Taylor
    Introducing the Special Issue of Machine Learning Selected from Papers Presented at the 1997 Conference on Computational Learning Theory, COLT'97. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1999, v:35, n:3, pp:191-192 [Journal]
  102. Yves Van de Peer, John Shawe-Taylor, Jayabalan Joseph, Axel Meyer
    Wanda: a database of duplicated fish genes. [Citation Graph (0, 0)][DBLP]
    Nucleic Acids Research, 2002, v:30, n:1, pp:109-112 [Journal]
  103. David R. Hardoon, Sándor Szedmák, John Shawe-Taylor
    Canonical Correlation Analysis: An Overview with Application to Learning Methods. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:12, pp:2639-2664 [Journal]
  104. Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alex J. Smola, Robert C. Williamson
    Estimating the Support of a High-Dimensional Distribution. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:7, pp:1443-1471 [Journal]
  105. John Shawe-Taylor, Martin Anthony, Walter Kern
    Classes of feedforward neural networks and their circuit complexity. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1992, v:5, n:6, pp:971-977 [Journal]
  106. John Shawe-Taylor, David A. Cohen
    Linear programming algorithm for neural networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1990, v:3, n:5, pp:575-582 [Journal]
  107. Jieyu Zhao, John Shawe-Taylor, Max van Daalen
    Learning in Stochastic Bit Stream Neural Networks. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1996, v:9, n:6, pp:991-998 [Journal]
  108. Shutao Li, John Shawe-Taylor
    Comparison and fusion of multiresolution features for texture classification. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2005, v:26, n:5, pp:633-638 [Journal]
  109. Jeffrey Wood, John Shawe-Taylor
    A unifying framework for invariant pattern recognition. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1996, v:17, n:14, pp:1415-1422 [Journal]
  110. John Shawe-Taylor, Tomaz Pisanski
    Homeomorphism of 2-Complexes is Graph Isomorphism Complete. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1994, v:23, n:1, pp:120-132 [Journal]
  111. Jong Yong Kim, John Shawe-Taylor
    Fast String Matching using an n -gram Algorithm. [Citation Graph (0, 0)][DBLP]
    Softw., Pract. Exper., 1994, v:24, n:1, pp:79-88 [Journal]
  112. Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson
    Covering numbers for support vector machines. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2002, v:48, n:1, pp:239-250 [Journal]
  113. Peter Jeavons, David A. Cohen, John Shawe-Taylor
    Generating binary sequences for stochastic computing. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1994, v:40, n:3, pp:716-720 [Journal]
  114. John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony
    Structural Risk Minimization Over Data-Dependent Hierarchies. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1998, v:44, n:5, pp:1926-1940 [Journal]
  115. John Shawe-Taylor, Nello Cristianini
    On the generalization of soft margin algorithms. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2002, v:48, n:10, pp:2721-2735 [Journal]
  116. John Shawe-Taylor, Christopher K. I. Williams, Nello Cristianini, Jaz S. Kandola
    On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2005, v:51, n:7, pp:2510-2522 [Journal]
  117. Petroula Tsampouka, John Shawe-Taylor
    Approximate maximum margin algorithms with rules controlled by the number of mistakes. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:903-910 [Conf]
  118. Amiran Ambroladze, Emilio Parrado-Hernández, John Shawe-Taylor
    Tighter PAC-Bayes Bounds. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:9-16 [Conf]
  119. Tomaz Pisanski, John Shawe-Taylor
    Search for minimal trivalent cycle permutation graphs with girth nine. [Citation Graph (0, 0)][DBLP]
    Discrete Mathematics, 1981, v:36, n:1, pp:113-115 [Journal]
  120. John Shawe-Taylor
    Coverings of complete bipartite graphs and associated structures. [Citation Graph (0, 0)][DBLP]
    Discrete Mathematics, 1994, v:134, n:1-3, pp:151-160 [Journal]
  121. Sándor Szedmák, John Shawe-Taylor
    Synthesis of maximum margin and multiview learning using unlabeled data. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2007, v:70, n:7-9, pp:1254-1264 [Journal]
  122. Yaoyong Li, John Shawe-Taylor
    Advanced learning algorithms for cross-language patent retrieval and classification. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Manage., 2007, v:43, n:5, pp:1183-1199 [Journal]
  123. Amiran Ambroladze, Emilio Parrado-Hernández, John Shawe-Taylor
    Complexity of pattern classes and the Lipschitz property. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2007, v:382, n:3, pp:232-246 [Journal]

  124. Distribution-Dependent PAC-Bayes Priors. [Citation Graph (, )][DBLP]


  125. A PAC-Bayes Bound for Tailored Density Estimation. [Citation Graph (, )][DBLP]


  126. Learning relevant eye movement feature spaces across users. [Citation Graph (, )][DBLP]


  127. Using Generalization Error Bounds to Train the Set Covering Machine. [Citation Graph (, )][DBLP]


  128. Using Image Stimuli to Drive fMRI Analysis. [Citation Graph (, )][DBLP]


  129. Kernel Regression Based Machine Translation. [Citation Graph (, )][DBLP]


  130. Variational Inference for Diffusion Processes. [Citation Graph (, )][DBLP]


  131. Theory of matching pursuit. [Citation Graph (, )][DBLP]


  132. Constructing Nonlinear Discriminants from Multiple Data Views. [Citation Graph (, )][DBLP]


  133. Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. [Citation Graph (, )][DBLP]


  134. Sensor placement and coordination via distributed multi-agent cooperative control. [Citation Graph (, )][DBLP]


  135. Technical perspective - Machine learning for complex predictions. [Citation Graph (, )][DBLP]


  136. GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. [Citation Graph (, )][DBLP]


  137. GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. [Citation Graph (, )][DBLP]


  138. Pattern analysis for the prediction of fungal pro-peptide cleavage sites. [Citation Graph (, )][DBLP]


  139. Guest editors' introduction: special issue of selected papers from ECML PKDD 2009. [Citation Graph (, )][DBLP]


Search in 0.142secs, Finished in 0.147secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
Introduction Collection Based Clustering Ranking Paper Based Journals Conferences DB Status Statistics Search
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002