Publikationen von A Zien
Alle Typen
Vortrag (5)
21.
Vortrag
Large Scale Machine Learning for Genomic Sequence Analysis (Support Vector Machine Based Signal Detectors). Eberhard-Karls-Universität, Tübingen, Germany (2009)
22.
Vortrag
Accurate and Interpretable Large Scale Genomic Signal Detection (Support Vector Machine Based Signal Detectors). Max-Planck-Institut für Molekulare Genetik, Berlin, Germany (2009)
23.
Vortrag
Positional Oligomer Importance Matrices. NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007), Whistler, BC, Canada (2007)
24.
Vortrag
Ab-initio gene finding using machine learning. NIPS 2006 Workshop on New Problems and Methods in Computational Biology (MLCB 2006), Vancouver, BC, Canada (2006)
Poster (3)
25.
Poster
RNA secondary structure prediction using large margin methods. 15th Annual International Conference on Intelligent Systems for Molecular Biology & 6th European Conference on Computational Biology (ISMB/ECCB 2007), Wien, Austria (2007)
26.
Poster
mGene: A Novel Discriminative Gene Finding System. 15th Annual International Conference on Intelligent Systems for Molecular Biology, 6th Annual European Conference on Computational Biology (ISMB/ECCB 2007), Wien, Austria (2007)
27.
Poster
An Automated Combination of Sequence Motif Kernels for Protein Subcellular Localization. 14th International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Fortaleza, Brazil (2006)
Bericht (5)
28.
Bericht
Non-Sparse Regularization and Efficient Training with Multiple Kernels. Electrical Engineering and Computer Sciences: University of California at Berkeley, Berkeley, CA, USA (2010), 43 S.
29.
Bericht
014-2009). (2009)
A Multi-Class Support Vector Machine Based on Scatter Criteria (Forschungsberichte der Fakultät IV: Elektrotechnik und Informatik, Technische Universität Berlin, 30.
Bericht
2/2007). (2007), 12 S.
Computing Positional Oligomer Importance Matrices (POIMs) (FIRST Reports, 31.
Bericht
150). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 9 S.
Towards the Inference of Graphs on Ordered Vertexes (Technical Report of the Max Planck Institute for Biological Cybernetics, 32.
Bericht
146). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 18 S.
An Automated Combination of Sequence Motif Kernels for Predicting Protein Subcellular Localization (Technical Report of the Max Planck Institute for Biological Cybernetics, Preprint (1)
33.
Preprint
Non-Sparse Regularization for Multiple Kernel Learning. (eingereicht)