Publikationen von AJ Smola

Thoma, M.; Cheng, H.; Gretton, A.; Han, J.; Kriegel, H.-P.; Smola, A.; Song, L.; Yu, P.; Yan, X.; Borgwardt, K.: Discriminative frequent subgraph mining with optimality guarantees. Statistical Analysis and Data Mining 3 (5), S. 302 - 318 (2010)

Gretton, A.; Herbrich, R.; Smola, A.; Bousquet, O.; Schölkopf, B.: Kernel Methods for Measuring Independence. The Journal of Machine Learning Research 6, S. 2075 - 2129 (2005)

Ong, C.; Smola, A.; Williamson, R.: Learning the Kernel with Hyperkernels. The Journal of Machine Learning Research 6, S. 1043 - 1071 (2005)

Chalimourda, A.; Schölkopf, B.; Smola, A.: Experimentally optimal ν in support vector regression for different noise models and parameter settings. Neural networks 18 (2), S. 205 - 205 (2005)

Smola, A.; Schölkopf, B.: A Tutorial on Support Vector Regression. Statistics and Computing 14 (3), S. 199 - 222 (2004)

Chalimourda, A.; Schölkopf, B.; Smola, A.: Experimentally optimal ν in support vector regression for different noise models and parameter settings. Neural networks 17 (1), S. 127 - 141 (2004)

Graf, A.; Smola, A.; Borer, S.: Classification in a Normalized Feature Space using Support Vector Machines. IEEE Transactions on Neural Networks 14 (3), S. 597 - 605 (2003)

Mika, S.; Rätsch, G.; Weston, J.; Schölkopf, B.; Smola, A.; Müller, K.-R.: Constructing descriptive and discriminative nonlinear features: Rayleigh coefficients in kernel feature spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (5), S. 623 - 628 (2003)

Schölkopf, B.; Mika, S.; Burges, C.; Knirsch, P.; Müller, K.-R.; Rätsch, G.; Smola, A.: Input space versus feature space in kernel-based methods. IEEE Transactions on Neural Networks 10 (5), S. 1000 - 1017 (1999)

Smola, A.; Schölkopf, B.: On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. Algorithmica 22 (1-2), S. 211 - 231 (1998)

Schölkopf, B.; Smola, A.; Müller, K.-R.: Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural computation 10 (5), S. 1299 - 1319 (1998)

Schölkopf, B.; Smola, A.: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge, MA, USA (2002), 626 S.

Gretton, A.; Smola, A.; Huang, J.; Schmittfull, M.; Borgwardt, K.; Schölkopf, B.: Covariate Shift by Kernel Mean Matching. In: Dataset Shift in Machine Learning, 8, S. 131 - 160 (Hg. Quiñonero-Candela, J.; Sugiyama, M.; Schwaighofer, A.; Lawrence, N.). MIT Press, Cambridge, MA, USA (2009)

Schölkopf, B.; Smola, A.: Support Vector Machines and Kernel Algorithms. In: Encyclopedia of Biostatistics, Bd. 8, 2. Aufl., S. 5328 - 5335 (Hg. Armitage, P.; Colton, T.). Wiley, Chichester, UK (2005)

Schölkopf, B.; Smola, A.: Support Vector Machines. In: Handbook of Brain Theory and Neural Networks, 2. Aufl., S. 1119 - 1125 (Hg. Arbib, M.). MIT Press, Cambridge, MA, USA (2003)

Advances in Kernel Methods: Support Vector Learning. Eleventh Annual Conference on Neural Information Processing (NIPS 1997), Breckenridge, CO, USA, 01. Dezember 1997 - 06. Dezember 1997. MIT Press, Cambridge, MA, USA (1999), 376 S.

Thoma, M.; Cheng, H.; Gretton, A.; Han, J.; Kriegel, H.-P.; Smola, A.; Song, L.; Yu, P.; Yan, X.; Borgwardt, K.: Near-optimal supervised feature selection among frequent subgraphs. In: 9th SIAM Conference on Data Mining (SDM 2009), S. 1076 - 1087 (Hg. Park, H.; Parthasarathy, S.; Liu, H.). 9th SIAM Conference on Data Mining (SDM 2009), Sparks, NV, USA, 30. April 2009 - 02. Mai 2009. Philadelphia, PA, USA, Society for Industrial and Applied Mathematics (2009)

Gretton, A.; Fukumizu, K.; Teo, C.; Song , L.; Schölkopf, B.; Smola, A.: A Kernel Statistical Test of Independence. In: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007, S. 585 - 592 (Hg. Platt, J.; Koller, D.; Singer, Y.; Roweis, S.). Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Vancouver, BC, Canada, 03. Dezember 2007 - 06. Dezember 2007. Curran, Red Hook, NY, USA (2008)

Song, L.; Smola, A.; Borgwardt, K.; Gretton, A.: Colored Maximum Variance Unfolding. In: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007, S. 1385 - 1392 (Hg. Platt, C.; Koller, D.; Singer, Y.; Roweis, S.). Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Vancouver, BC, Canada, 03. Dezember 2007 - 06. Dezember 2007. Curran, Red Hook, NY, USA (2008)

Borgwardt, K.; Yan, X.; Thoma, M.; Cheng, H.; Gretton, A.; Song, L.; Smola, A.; Han, J.; Hu, P.; Kriegel, H.-P.: Combining near-optimal feature selection with gSpan. In: 6th International Workshop on Mining and Learning with Graphs (MLG 2008), S. 1 - 3. 6th International Workshop on Mining and Learning with Graphs (MLG 2008), Helsinki, Finland, 04. Juli 2008 - 05. Juli 2008. (2008)