| 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 | 5224 | 2001 |
| New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000 | 3156 | 2000 |
| A Generalized Representer Theorem B Scholkopf, R Herbrich, A Smola, R Williamson | 1572 | 2000 |
| Support vector method for novelty detection. B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt NIPS 12, 582-588, 1999 | 1549 | 1999 |
| Online learning with kernels J Kivinen, AJ Smola, RC Williamson IEEE transactions on signal processing 52 (8), 2165-2176, 2004 | 1158 | 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 | 660 | 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 | 482 | 1990 |
| Learning the kernel with hyperkernels CS Ong, A Smola, B Williamson Journal of Machine Learning Research 6, 1045-1071, 2005 | 413 | 2005 |
| 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 | 401 | 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 | 346 | 1995 |
| Clustering: Science or art? U von Luxburg, R Williamson, I Guyon Journal of Machine Learning Research 27, 65-80, 2012 | 298* | 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 | 228 | 1999 |
| The need for open source software in machine learning S Sonnenburg, ML Braun, CS Ong, S Bengio, L Bottou, G Holmes, ... | 210 | 2007 |
| 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 | 203 | 2001 |
| 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 | 191 | 1996 |
| 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 | 183 | 1996 |
| Support vector regression with automatic accuracy control B Schölkopf, P Bartlett, A Smola, R Williamson International conference on artificial neural networks, 111-116, 1998 | 174 | 1998 |
| Equalization in an acoustic reverberant environment: Robustness results BD Radlovic, RC Williamson, RA Kennedy IEEE Transactions on Speech and Audio Processing 8 (3), 311-319, 2000 | 169 | 2000 |
| The statistical performance of some instantaneous frequency estimators BC Lovell, RC Williamson IEEE Transactions on Signal Processing 40 (7), 1708-1723, 1992 | 166 | 1992 |
| Composite binary losses MD Reid, RC Williamson The Journal of Machine Learning Research 11, 2387-2422, 2010 | 164 | 2010 |
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