| 2008 |
|---|
| 9 | EE | Tobias Glasmachers:
On related violating pairs for working set selection in SMO algorithms.
ESANN 2008: 475-480 |
| 8 | EE | Tobias Glasmachers,
Christian Igel:
Uncertainty Handling in Model Selection for Support Vector Machines.
PPSN 2008: 185-194 |
| 7 | EE | Tobias Glasmachers,
Christian Igel:
Second-Order SMO Improves SVM Online and Active Learning.
Neural Computation 20(2): 374-382 (2008) |
| 2007 |
|---|
| 6 | EE | Christian Igel,
Tobias Glasmachers,
Britta Mersch,
Nico Pfeifer,
Peter Meinicke:
Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection.
IEEE/ACM Trans. Comput. Biology Bioinform. 4(2): 216-226 (2007) |
| 5 | EE | Britta Mersch,
Tobias Glasmachers,
Peter Meinicke,
Christian Igel:
Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts.
Int. J. Neural Syst. 17(5): 369-381 (2007) |
| 2006 |
|---|
| 4 | EE | Tobias Glasmachers:
Degeneracy in model selection for SVMs with radial Gaussian kernel.
ESANN 2006: 587-592 |
| 3 | EE | Britta Mersch,
Tobias Glasmachers,
Peter Meinicke,
Christian Igel:
Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts.
ICANN (2) 2006: 827-836 |
| 2 | EE | Tobias Glasmachers,
Christian Igel:
Maximum-Gain Working Set Selection for SVMs.
Journal of Machine Learning Research 7: 1437-1466 (2006) |
| 2005 |
|---|
| 1 | EE | Tobias Glasmachers,
Christian Igel:
Gradient-Based Adaptation of General Gaussian Kernels.
Neural Computation 17(10): 2099-2105 (2005) |
