| Scaling learning algorithms towards AI Y Bengio, Y LeCun Large-scale kernel machines 34 (5), 1-41, 2007 | 1717 | 2007 |
| Training invariant support vector machines D DeCoste, B Scholkopf | 801 | 2002 |
| HD-CNN: hierarchical deep convolutional neural networks for large scale visual recognition Z Yan, H Zhang, R Piramuthu, V Jagadeesh, D DeCoste, W Di, Y Yu Proceedings of the IEEE international conference on computer vision, 2740-2748, 2015 | 522* | 2015 |
| A modified finite Newton method for fast solution of large scale linear SVMs. SS Keerthi, D DeCoste, T Joachims Journal of Machine Learning Research 6 (3), 2005 | 400 | 2005 |
| Machine learning for science: state of the art and future prospects E Mjolsness, D DeCoste science 293 (5537), 2051-2055, 2001 | 394 | 2001 |
| Building support vector machines with reduced classifier complexity. SS Keerthi, O Chapelle, D DeCoste, KP Bennett, E Parrado-Hernández Journal of Machine Learning Research 7 (7), 2006 | 375 | 2006 |
| Naïve filterbots for robust cold-start recommendations ST Park, D Pennock, O Madani, N Good, D DeCoste Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 250 | 2006 |
| Large-scale kernel machines L Bottou, O Chapelle, D Decoste, J Weston MIT press, 2007 | 214 | 2007 |
| Dynamic across-time measurement interpretation D DeCoste Artificial Intelligence 51 (1-3), 273-341, 1991 | 162 | 1991 |
| Collaborative prediction using ensembles of maximum margin matrix factorizations D DeCoste Proceedings of the 23rd international conference on Machine learning, 249-256, 2006 | 131 | 2006 |
| Alpha seeding for support vector machines D DeCoste, K Wagstaff Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 105 | 2000 |
| An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels MMS Lee, SS Keerthi, CJ Ong, D DeCoste IEEE Transactions on Neural Networks 15 (3), 750-757, 2004 | 93 | 2004 |
| Visualizing data mining models K Thearling, B Becker, D DeCoste, B Mawby, M Pilote, D Sommerfield Information visualization in data mining and knowledge discovery 24, 205-222, 2001 | 93 | 2001 |
| Compact random feature maps R Hamid, Y Xiao, A Gittens, D DeCoste International conference on machine learning, 19-27, 2014 | 85 | 2014 |
| Large-scale kernel machines Y Bengio, Y LeCun, L Bottou, O Chapelle, D DeCoste, J Weston Scaling Learning Algorithms towards AI. MIT Press, Cambridge, 2007 | 57 | 2007 |
| Ensembles of nearest neighbor forecasts D Yankov, D DeCoste, E Keogh Machine Learning: ECML 2006: 17th European Conference on Machine Learning …, 2006 | 54 | 2006 |
| Data parameters: A new family of parameters for learning a differentiable curriculum S Saxena, O Tuzel, D DeCoste Advances in Neural Information Processing Systems 32, 2019 | 52 | 2019 |
| Percentage based online advertising GW Flake, BD Brewer, DM DeCoste US Patent App. 11/734,134, 2008 | 50 | 2008 |
| Automated learning and monitoring of limit functions D DeCoste International Symposium on Artificial Intelligence, Robotics, and Automation …, 1997 | 47 | 1997 |
| Rover traverse science for increased mission science return R Castano, RC Anderson, T Estlin, D DeCoste, F Fisher, D Gaines, ... Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space …, 2003 | 46 | 2003 |
Olivier ChapelleGoogleVerified email at chapelle.cc
