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Robert C. Williamson: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson
    Learnability of Probabilistic Automata via Oracles. [Citation Graph (0, 0)][DBLP]
    ALT, 2005, pp:171-182 [Conf]
  2. Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
    Large Margin Classification for Moving Targets. [Citation Graph (0, 0)][DBLP]
    ALT, 2002, pp:113-127 [Conf]
  3. Peter L. Bartlett, Robert C. Williamson
    Investigating the Distribution Assumptions in the Pac Learning Model. [Citation Graph (0, 0)][DBLP]
    COLT, 1991, pp:24-32 [Conf]
  4. Kim L. Blackmore, Robert C. Williamson, Iven M. Y. Mareels, William A. Sethares
    Online Learning via Congregational Gradient Descent. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:265-272 [Conf]
  5. Peter L. Bartlett, Philip M. Long, Robert C. Williamson
    Fat-Shattering and the Learnability of Real-Valued Functions. [Citation Graph (0, 0)][DBLP]
    COLT, 1994, pp:299-310 [Conf]
  6. 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]
  7. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 1994, pp:362-367 [Conf]
  8. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    On Efficient Agnostic Learning of Linear Combinations of Basis Functions. [Citation Graph (0, 0)][DBLP]
    COLT, 1995, pp:369-376 [Conf]
  9. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    The Importance of Convexity in Learning with Squared Loss. [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:140-146 [Conf]
  10. Shahar Mendelson, Robert C. Williamson
    Agnostic Learning Nonconvex Function Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 2002, pp:1-13 [Conf]
  11. 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]
  12. John Shawe-Taylor, Robert C. Williamson
    A PAC Analysis of a Bayesian Estimator. [Citation Graph (0, 0)][DBLP]
    COLT, 1997, pp:2-9 [Conf]
  13. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Entropy Numbers of Linear Function Classes. [Citation Graph (0, 0)][DBLP]
    COLT, 2000, pp:309-319 [Conf]
  14. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Entropy Numbers, Operators and Support Vector Kernels. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:285-299 [Conf]
  15. Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
    Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP]
    EuroCOLT, 1999, pp:214-229 [Conf]
  16. Thore Graepel, Ralf Herbrich, Robert C. Williamson
    From Margin to Sparsity. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:210-216 [Conf]
  17. Uwe Helmke, Robert C. Williamson
    Rational Parametrizations of Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:623-630 [Conf]
  18. Ralf Herbrich, Robert C. Williamson
    Algorithmic Luckiness. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:391-397 [Conf]
  19. Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
    Online Learning with Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:785-792 [Conf]
  20. Adam Kowalczyk, Jacek Szymanski, Peter L. Bartlett, Robert C. Williamson
    Examples of learning curves from a modified VC-formalism. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:344-350 [Conf]
  21. Adam Kowalczyk, Alex J. Smola, Robert C. Williamson
    Kernel Machines and Boolean Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:439-446 [Conf]
  22. Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
    Hyperkernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:478-485 [Conf]
  23. Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson
    Shrinking the Tube: A New Support Vector Regression Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:330-336 [Conf]
  24. 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]
  25. Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson
    Regularization with Dot-Product Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:308-314 [Conf]
  26. 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]
  27. Robert C. Williamson
    epsilon-Entropy and the Complexity of Feedforward Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:946-952 [Conf]
  28. Robert C. Williamson, Peter L. Bartlett
    Splines, Rational Functions and Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:1040-1047 [Conf]
  29. Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John C. Platt, Robert C. Williamson
    Online Bayes Point Machines. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2003, pp:241-252 [Conf]
  30. Robert C. Williamson, Tom Downs
    Probabilistic arithmetic. I. Numerical methods for calculating convolutions and dependency bounds. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1990, v:4, n:2, pp:89-158 [Journal]
  31. Robert C. Williamson
    An extreme limit theorem for dependency bounds of normalized sums of random variables. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1991, v:56, n:1-3, pp:113-141 [Journal]
  32. Peter L. Bartlett, Philip M. Long, Robert C. Williamson
    Fat-Shattering and the Learnability of Real-Valued Functions. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1996, v:52, n:3, pp:434-452 [Journal]
  33. Ralf Herbrich, Robert C. Williamson
    Algorithmic Luckiness. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:175-212 [Journal]
  34. Robert E. Mahony, Robert C. Williamson
    Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2001, v:1, n:, pp:311-355 [Journal]
  35. Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
    Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2001, v:1, n:, pp:179-209 [Journal]
  36. Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
    Learning the Kernel with Hyperkernels. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1043-1071 [Journal]
  37. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    Correction to 'Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes'. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:4, pp:765-769 [Journal]
  38. 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]
  39. Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett
    New Support Vector Algorithms. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:5, pp:1207-1245 [Journal]
  40. Kim L. Blackmore, Robert C. Williamson, Iven M. Y. Mareels
    Decision region approximation by polynomials or neural networks. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1997, v:43, n:3, pp:903-907 [Journal]
  41. 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]
  42. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    Efficient agnostic learning of neural networks with bounded fan-in. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1996, v:42, n:6, pp:2118-2132 [Journal]
  43. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson
    The Importance of Convexity in Learning with Squared Loss. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 1998, v:44, n:5, pp:1974-1980 [Journal]
  44. 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]
  45. Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
    Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2001, v:47, n:6, pp:2516-2532 [Journal]

  46. Surrogate regret bounds for proper losses. [Citation Graph (, )][DBLP]


  47. Generalised Pinsker Inequalities [Citation Graph (, )][DBLP]


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