| Drug design by machine learning: support vector machines for pharmaceutical data analysis R Burbidge, M Trotter, B Buxton, S Holden Computers & chemistry 26 (1), 5-14, 2001 | 944 | 2001 |
| 3D analysis of facial morphology P Hammond, TJ Hutton, JE Allanson, LE Campbell, RCM Hennekam, ... American journal of medical genetics Part A 126 (4), 339-348, 2004 | 300 | 2004 |
| The generalized FITC approximation A Naish-Guzman, S Holden Advances in neural information processing systems 20, 2007 | 131 | 2007 |
| Machine learning for first-order theorem proving: learning to select a good heuristic JP Bridge, SB Holden, LC Paulson Journal of automated reasoning 53, 141-172, 2014 | 118 | 2014 |
| Support vector machines in combinatorial chemistry MWB Trotter, BF Buxton, SB Holden Measurement and Control 34 (8), 235-239, 2001 | 92 | 2001 |
| Performance degradation in boosting J Wickramaratna, S Holden, B Buxton Multiple Classifier Systems: Second International Workshop, MCS 2001 …, 2001 | 86 | 2001 |
| Learning from heterogeneous data sources: an application in spatial proteomics LM Breckels, SB Holden, D Wojnar, CM Mulvey, A Christoforou, A Groen, ... PLoS computational biology 12 (5), e1004920, 2016 | 66 | 2016 |
| Support vector machines for ADME property classification MWB Trotter, SB Holden Qsar & Combinatorial Science 22 (5), 533-548, 2003 | 61 | 2003 |
| Generalization and PAC learning: some new results for the class of generalized single-layer networks SB Holden, PJW Rayner IEEE Transactions on Neural Networks 6 (2), 368-380, 1995 | 52 | 1995 |
| Cross-validation for binary classification by real-valued functions: theoretical analysis M Anthony, SB Holden Proceedings of the eleventh annual conference on Computational learning …, 1998 | 48 | 1998 |
| On the practical applicability of VC dimension bounds SB Holden, M Niranjan Neural Computation 7 (6), 1265-1288, 1995 | 39 | 1995 |
| PAC-like upper bounds for the sample complexity of leave-one-out cross-validation SB Holden Proceedings of the ninth annual conference on Computational learning theory …, 1996 | 28 | 1996 |
| Modeling the model athlete: Automatic coaching of rowing technique S Fothergill, R Harle, S Holden Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2008 | 26 | 2008 |
| Robust regression with twinned Gaussian processes A Naish-Guzman, S Holden Advances in neural information processing systems 20, 2007 | 25 | 2007 |
| Machine learning for automated theorem proving: Learning to solve SAT and QSAT SB Holden Foundations and Trends® in Machine Learning 14 (6), 807-989, 2021 | 23 | 2021 |
| Quantifying generalization in linearly weighted neural networks M Anthony, SB Holden Complex Systems 8 (2), 91-114, 1994 | 23 | 1994 |
| Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation IM Armean, KS Lilley, MWB Trotter, NCV Pilkington, SB Holden Bioinformatics 34 (11), 1884-1892, 2018 | 20 | 2018 |
| Average-case learning curves for radial basis function networks SB Holden, M Niranjan Neural Computation 9 (2), 441-460, 1997 | 19 | 1997 |
| Cross-validation and the PAC Learning Model SB Holden Technical R eport RN/96/94, D ept. of Cs, Univ. College, L ondon, 1996 | 16 | 1996 |
| On the theory of generalization and self-structuring in linearly weighted connectionist networks. SB Holden University of Cambridge, 1993 | 16 | 1993 |
Lawrence PaulsonUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
