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
56142001
New support vector algorithms
B Schölkopf, AJ Smola, RC Williamson, PL Bartlett
Neural computation 12 (5), 1207-1245, 2000
32852000
Support vector method for novelty detection.
B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt
NIPS 12, 582-588, 1999
17681999
A Generalized Representer Theorem
B Scholkopf, R Herbrich, A Smola, R Williamson
17012000
Online learning with kernels
J Kivinen, AJ Smola, RC Williamson
IEEE transactions on signal processing 52 (8), 2165-2176, 2004
12132004
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
6841998
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
4262005
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
4092003
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
3511995
Clustering: Science or art?
U von Luxburg, R Williamson, I Guyon
Journal of Machine Learning Research 27, 65-80, 2012
326*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
2351999
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
2312007
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
The cost of fairness in binary classification
AK Menon, RC Williamson
Conference on Fairness, Accountability and Transparency, 107-118, 2018
1792018
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
1772011
Composite binary losses
MD Reid, RC Williamson
The Journal of Machine Learning Research 11, 2387-2422, 2010
1772010
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