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
56972001
New support vector algorithms
B Schölkopf, AJ Smola, RC Williamson, PL Bartlett
Neural computation 12 (5), 1207-1245, 2000
33112000
Support vector method for novelty detection.
B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt
NIPS 12, 582-588, 1999
18261999
A Generalized Representer Theorem
B Scholkopf, R Herbrich, A Smola, R Williamson
17182000
Online learning with kernels
J Kivinen, AJ Smola, RC Williamson
IEEE transactions on signal processing 52 (8), 2165-2176, 2004
12182004
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
6881998
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
5011990
Learning the kernel with hyperkernels
CS Ong, A Smola, B Williamson
Journal of Machine Learning Research 6, 1045-1071, 2005
4302005
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
4112003
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
3541995
Clustering: Science or art?
U von Luxburg, R Williamson, I Guyon
Journal of Machine Learning Research 27, 65-80, 2012
338*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
2391999
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
2342007
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
2082001
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
2011996
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
1941996
The cost of fairness in binary classification
AK Menon, RC Williamson
Conference on Fairness, Accountability and Transparency, 107-118, 2018
1922018
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
1821997
Information, divergence and risk for binary experiments
M Reid, R Williamson
MIT Press, 2011
1812011
Learning with symmetric label noise: The importance of being unhinged
B Van Rooyen, AK Menon, RC Williamson
arXiv preprint arXiv:1505.07634, 2015
1792015
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