Learning with kernels: Support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola the MIT Press, 2002 | 24364* | 2002 |
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004 | 15341 | 2004 |
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998 | 10920 | 1998 |
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 | 7229 | 2001 |
Support vector regression machines H Drucker, CJ Burges, L Kaufman, A Smola, V Vapnik Advances in neural information processing systems 9, 1996 | 6690 | 1996 |
Hierarchical attention networks for document classification Z Yang, D Yang, C Dyer, X He, A Smola, E Hovy Proceedings of the 2016 conference of the North American chapter of the …, 2016 | 5814 | 2016 |
A kernel two-sample test A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, A Smola The Journal of Machine Learning Research 13 (1), 723-773, 2012 | 5498 | 2012 |
Support vector method for function approximation, regression estimation and signal processing V Vapnik, S Golowich, A Smola Advances in neural information processing systems 9, 1996 | 4284 | 1996 |
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000 | 3747 | 2000 |
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997 | 3391 | 1997 |
Support vector method for novelty detection B Schölkopf, RC Williamson, A Smola, J Shawe-Taylor, J Platt Advances in neural information processing systems 12, 1999 | 2976 | 1999 |
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola | 2830 | 2008 |
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017 | 2683 | 2017 |
Advances in kernel methods: support vector learning B Schölkopf, CJC Burges, AJ Smola MIT press, 1999 | 2639 | 1999 |
A kernel method for the two-sample-problem A Gretton, K Borgwardt, M Rasch, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 2558 | 2006 |
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001 | 2260 | 2001 |
Stacked attention networks for image question answering Z Yang, X He, J Gao, L Deng, A Smola Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2242 | 2016 |
Scaling distributed machine learning with the parameter server M Li, DG Andersen, JW Park, AJ Smola, A Ahmed, V Josifovski, J Long, ... 11th USENIX Symposium on operating systems design and implementation (OSDI …, 2014 | 2159 | 2014 |
kernlab-an S4 package for kernel methods in R A Karatzoglou, A Smola, K Hornik, A Zeileis Journal of statistical software 11, 1-20, 2004 | 2146 | 2004 |
Correcting sample selection bias by unlabeled data J Huang, A Gretton, K Borgwardt, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 2129 | 2006 |