Robert C. Williamson
Robert C. Williamson
Verified email at uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
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
55612001
New support vector algorithms
B Schölkopf, AJ Smola, RC Williamson, PL Bartlett
Neural computation 12 (5), 1207-1245, 2000
32732000
Support vector method for novelty detection.
B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt
NIPS 12, 582-588, 1999
17381999
A Generalized Representer Theorem
B Scholkopf, R Herbrich, A Smola, R Williamson
16882000
Online learning with kernels
J Kivinen, AJ Smola, RC Williamson
IEEE transactions on signal processing 52 (8), 2165-2176, 2004
12082004
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
6811998
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
4991990
Learning the kernel with hyperkernels
CS Ong, A Smola, B Williamson
Journal of Machine Learning Research 6, 1045-1071, 2005
4252005
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
4082003
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
3501995
Clustering: Science or art?
U von Luxburg, R Williamson, I Guyon
Journal of Machine Learning Research 27, 65-80, 2012
325*2012
Shrinking the tube: a new support vector regression algorithm
B Scholkopf, PL Bartlett, AJ Smola, R Williamson
Advances in neural information processing systems, 330-336, 1999
2341999
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
2302007
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
2072001
Efficient agnostic learning of neural networks with bounded fan-in
WS Lee, PL Bartlett, RC Williamson
IEEE Transactions on Information Theory 42 (6), 2118-2132, 1996
2001996
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
1901996
Support vector regression with automatic accuracy control
B Schölkopf, P Bartlett, A Smola, R Williamson
International conference on artificial neural networks, 111-116, 1998
1791998
Information, divergence and risk for binary experiments
M Reid, R Williamson
MIT Press, 2011
1762011
Composite binary losses
MD Reid, RC Williamson
The Journal of Machine Learning Research 11, 2387-2422, 2010
1752010
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
1751997
The system can't perform the operation now. Try again later.
Articles 1–20