Tobias Glasmachers
Tobias Glasmachers
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Cited by
Cited by
C Igel, V Heidrich-Meisner, T Glasmachers
Journal of machine learning research 9 (Jun), 993-996, 2008
Natural evolution strategies
D Wierstra, T Schaul, T Glasmachers, Y Sun, J Peters, J Schmidhuber
The Journal of Machine Learning Research 15 (1), 949-980, 2014
Exponential natural evolution strategies
T Glasmachers, T Schaul, S Yi, D Wierstra, J Schmidhuber
Proceedings of the 12th annual conference on Genetic and evolutionary†…, 2010
Maximum-gain working set selection for SVMs
T Glasmachers, C Igel
The Journal of Machine Learning Research 7, 1437-1466, 2006
Gradient-based adaptation of general Gaussian kernels
T Glasmachers, C Igel
Neural Computation 17 (10), 2099-2105, 2005
High dimensions and heavy tails for natural evolution strategies
T Schaul, T Glasmachers, J Schmidhuber
Proceedings of the 13th annual conference on Genetic and evolutionary†…, 2011
Gradient-based optimization of kernel-target alignment for sequence kernels applied to bacterial gene start detection
C Igel, T Glasmachers, B Mersch, N Pfeifer, P Meinicke
IEEE/ACM Transactions on Computational Biology and Bioinformatics 4 (2), 216-226, 2007
A unified view on multi-class support vector classification
‹ Doǧan, T Glasmachers, C Igel
The Journal of Machine Learning Research 17 (1), 1550-1831, 2016
Limits of end-to-end learning
T Glasmachers
arXiv preprint arXiv:1704.08305, 2017
Maximum likelihood model selection for 1-norm soft margin SVMs with multiple parameters
T Glasmachers, C Igel
IEEE transactions on pattern analysis and machine intelligence 32 (8), 1522-1528, 2010
Second-order SMO improves SVM online and active learning
T Glasmachers, C Igel
Neural Computation 20 (2), 374-382, 2008
Evolutionary optimization of sequence kernels for detection of bacterial gene starts
B Mersch, T Glasmachers, P Meinicke, C Igel
International Journal of Neural Systems 17 (5), 369-381, 2007
A natural evolution strategy for multi-objective optimization
T Glasmachers, T Schaul, J Schmidhuber
International Conference on Parallel Problem Solving from Nature, 627-636, 2010
Novelty-based restarts for evolution strategies
G Cuccu, F Gomez, T Glasmachers
2011 IEEE Congress of Evolutionary Computation (CEC), 158-163, 2011
Accelerated coordinate descent with adaptive coordinate frequencies
T Glasmachers, U Dogan
Asian Conference on Machine Learning, 72-86, 2013
A comparative study on large scale kernelized support vector machines
D Horn, A Demircioğlu, B Bischl, T Glasmachers, C Weihs
Advances in Data Analysis and Classification 12 (4), 867-883, 2018
Large scale black-box optimization by limited-memory matrix adaptation
I Loshchilov, T Glasmachers, HG Beyer
IEEE Transactions on Evolutionary Computation 23 (2), 353-358, 2018
Artificial curiosity for autonomous space exploration
V Graziano, T Glasmachers, T Schaul, L Pape, G Cuccu, J Leitner, ...
Acta Futura 4, 41-51, 2011
Unbounded population MO-CMA-ES for the bi-objective BBOB test suite
O Krause, T Glasmachers, N Hansen, C Igel
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference†…, 2016
Coherence progress: a measure of interestingness based on fixed compressors
T Schaul, L Pape, T Glasmachers, V Graziano, J Schmidhuber
International Conference on Artificial General Intelligence, 21-30, 2011
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