Robert C. Williamson
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Cited by
Estimating the support of a high-dimensional distribution
B Schölkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson
Neural computation 13 (7), 1443-1471, 2001
New support vector algorithms
B Schölkopf, AJ Smola, RC Williamson, PL Bartlett
Neural computation 12 (5), 1207-1245, 2000
Support vector method for novelty detection
B Schölkopf, RC Williamson, A Smola, J Shawe-Taylor, J Platt
Advances in neural information processing systems 12, 1999
A Generalized Representer Theorem
B Scholkopf, R Herbrich, A Smola, R Williamson
Online learning with kernels
J Kivinen, AJ Smola, RC Williamson
IEEE transactions on signal processing 52 (8), 2165-2176, 2004
Structural risk minimization over data-dependent hierarchies
J Shawe-Taylor, PL Bartlett, RC Williamson, M Anthony
IEEE transactions on Information Theory 44 (5), 1926-1940, 1998
Probabilistic arithmetic. I. Numerical methods for calculating convolutions and dependency bounds
RC Williamson, T Downs
International journal of approximate reasoning 4 (2), 89-158, 1990
Clustering: Science or art?
U von Luxburg, R Williamson, I Guyon
Journal of Machine Learning Research 27, 65-80, 2012
Learning the kernel with hyperkernels
CS Ong, A Smola, B Williamson
Journal of Machine Learning Research 6, 1045-1071, 2005
The cost of fairness in binary classification
AK Menon, RC Williamson
Conference on Fairness, accountability and transparency, 107-118, 2018
Particle filtering algorithms for tracking an acoustic source in a reverberant environment
DB Ward, EA Lehmann, RC Williamson
IEEE Transactions on speech and audio processing 11 (6), 826-836, 2003
Theory and design of broadband sensor arrays with frequency invariant far‐field beam patterns
DB Ward, RA Kennedy, RC Williamson
The Journal of the Acoustical Society of America 97 (2), 1023-1034, 1995
Learning with symmetric label noise: The importance of being unhinged
B Van Rooyen, A Menon, RC Williamson
Advances in neural information processing systems 28, 2015
A PAC analysis of a Bayesian estimator
J Shawe-Taylor, RC Williamson
Proceedings of the tenth annual conference on Computational learning theory, 2-9, 1997
The need for open source software in machine learning
S Sonnenburg, ML Braun, CS Ong, S Bengio, L Bottou, G Holmes, ...
JMLR 8, 2443-2466, 2007
Learning from corrupted binary labels via class-probability estimation
A Menon, B Van Rooyen, CS Ong, B Williamson
International conference on machine learning, 125-134, 2015
Shrinking the tube: a new support vector regression algorithm
B Schölkopf, P Bartlett, A Smola, RC Williamson
Advances in neural information processing systems 11, 1998
Composite binary losses
MD Reid, RC Williamson
The Journal of Machine Learning Research 11, 2387-2422, 2010
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators
RC Williamson, AJ Smola, B Scholkopf
IEEE transactions on Information Theory 47 (6), 2516-2532, 2001
Fat shattering and the learnability of real-valued functions
PL Bartlett, PM Long, RC Williamson
Journal of Computer and System Sciences 52 (3), 434-452, 1996
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