Sebastian Mika
Sebastian Mika
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TitleCited byYear
An introduction to kernel-based learning algorithms
KR Muller, S Mika, G Ratsch, K Tsuda, B Scholkopf
IEEE transactions on neural networks 12 (2), 181-201, 2001
41212001
Fisher discriminant analysis with kernels
S Mika, G Ratsch, J Weston, B Scholkopf, KR Mullers
Neural networks for signal processing IX: Proceedings of the 1999 IEEE …, 1999
30321999
Input space versus feature space in kernel-based methods
B Schölkopf, S Mika, CJC Burges, P Knirsch, KR Müller, G Rätsch, ...
IEEE transactions on neural networks 10 (5), 1000-1017, 1999
14601999
Kernel PCA and de-noising in feature spaces
S Mika, B Schölkopf, AJ Smola, KR Müller, M Scholz, G Rätsch
Advances in neural information processing systems, 536-542, 1999
10441999
Engineering support vector machine kernels that recognize translation initiation sites
A Zien, G Rätsch, S Mika, B Schölkopf, T Lengauer, KR Müller
Bioinformatics 16 (9), 799-807, 2000
5942000
A kernel view of the dimensionality reduction of manifolds
JH Ham, DD Lee, S Mika, B Schölkopf
Departmental Papers (ESE), 93, 2004
5722004
Constructing boosting algorithms from SVMs: An application to one-class classification
G Rätsch, S Mika, B Schölkopf, KR Müller
IEEE Transactions on Pattern Analysis & Machine Intelligence, 1184-1199, 2002
2722002
Invariant feature extraction and classification in kernel spaces
S Mika, G Rätsch, J Weston, B Schölkopf, AJ Smola, KR Müller
Advances in neural information processing systems, 526-532, 2000
2382000
Constructing descriptive and discriminative nonlinear features: Rayleigh coefficients in kernel feature spaces
S Mika, G Rätsch, J Weston, B Schölkopf, A Smola, KR Müller
IEEE Transactions on Pattern Analysis & Machine Intelligence, 623-633, 2003
2362003
A mathematical programming approach to the kernel fisher algorithm
S Mika, G Rätsch, KR Müller
Advances in neural information processing systems, 591-597, 2001
2282001
Benchmark data set for in silico prediction of Ames mutagenicity
K Hansen, S Mika, T Schroeter, A Sutter, A Ter Laak, T Steger-Hartmann, ...
Journal of chemical information and modeling 49 (9), 2077-2081, 2009
2142009
Kernel fisher discriminants
S Mika
1642003
Kernel PCA Pattern Reconstruction via Approximate Pre-Images
B Schölkopf, S Mika, A Smola, G Rätsch, KR Müller
International Conference on Artificial Neural Networks, 147-152, 1998
1361998
An improved training algorithm for kernel Fisher discriminants.
S Mika, AJ Smola, B Schölkopf
AISTATS, 98-104, 2001
1312001
Regularized principal manifolds
AJ Smola, S Mika, B Schölkopf, RC Williamson
Journal of Machine Learning Research 1 (Jun), 179-209, 2001
1022001
Classifying ‘drug-likeness' with kernel-based learning methods
KR Müller, G Rätsch, S Sonnenburg, S Mika, M Grimm, N Heinrich
Journal of chemical information and modeling 45 (2), 249-253, 2005
1012005
Accurate solubility prediction with error bars for electrolytes: A machine learning approach
A Schwaighofer, T Schroeter, S Mika, J Laub, A Ter Laak, D Sülzle, ...
Journal of chemical information and modeling 47 (2), 407-424, 2007
662007
Robust ensemble learning
G Rätsch, B Schölkopf, AJ Smola, S Mika, T Onoda, KR Müller
632000
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules
TS Schroeter, A Schwaighofer, S Mika, A Ter Laak, D Suelzle, U Ganzer, ...
Journal of Computer-aided molecular design 21 (9), 485-498, 2007
602007
Regularizing adaboost
G Rätsch, T Onoda, KR Müller
Advances in neural information processing systems, 564-570, 1999
551999
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