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ORCIDMadeleine Seeland
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2010 – 2019
- 2014
[b1]Madeleine Seeland:
Structural Graph Clustering: Scalable Methods and Applications for Graph Classification and Regression. Technical University Munich, 2014- [c8]Madeleine Seeland, Andreas Karwath
, Stefan Kramer:
Structural clustering of millions of molecular graphs. SAC 2014: 121-128 - [c7]Madeleine Seeland, Andreas Maunz, Andreas Karwath, Stefan Kramer:
Extracting information from support vector machines for pattern-based classification. SAC 2014: 129-136 - 2013
- [c6]Madeleine Seeland, Stefan Kramer, Bernhard Pfahringer:
Model selection based product kernel learning for regression on graphs. SAC 2013: 136-143 - 2012
- [c5]Madeleine Seeland, Andreas Karwath, Stefan Kramer:
A structural cluster kernel for learning on graphs. KDD 2012: 516-524 - [c4]Madeleine Seeland, Fabian Buchwald, Stefan Kramer, Bernhard Pfahringer:
Maximum Common Subgraph based locally weighted regression. SAC 2012: 165-172 - 2011
- [c3]Madeleine Seeland, Simon A. Berger, Alexandros Stamatakis, Stefan Kramer:
Parallel Structural Graph Clustering. ECML/PKDD (3) 2011: 256-272 - 2010
- [c2]Madeleine Seeland, Tobias Girschick, Fabian Buchwald, Stefan Kramer:
Online Structural Graph Clustering Using Frequent Subgraph Mining. ECML/PKDD (3) 2010: 213-228
2000 – 2009
- 2008
- [c1]Steffen Remmele, Madeleine Seeland, Jürgen Hesser:
Fluorescence Microscopy Deconvolution Based on Bregman Iteration and Richardson-Lucy Algorithm with TV Regularization. Bildverarbeitung für die Medizin 2008: 72-76
Coauthor Index
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