Publications

This folder holds the following references to publications, sorted by year and author.

There are 158 references in this bibliography folder.

Girschick, T, Rückert, U, and Kramer, S (accepted).
Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships and Data-Driven Selection of Source Datasets
The Computer Journal.

Hapfelmeier, A, Schmidt, J, and Kramer, S (2013).
Incremental Linear Model Trees on Massive Datasets: Keep it Simple, Keep it Fast
In: Proceedings of the 28th Symposium On Applied Computing, accepted.

Maunz, A, Gütlein, M, Rautenberg, M, Vorgrimmler, D, Gebele, D, and Helma, C (2013).
Lazar: A Modular Predictive Toxicology Framework
Frontiers in Pharmacology, 4(00038).

Maunz, A, Vorgrimmler, D, and Helma, C (2013).
Out-of-Bag Discriminative Graph Mining
In: Proceedings of the 28th Symposium On Applied Computing, accepted.

Schmidt, J, Hapfelmeier, A, Ghorbani, A, and Kramer, S (2013).
Learning Probabilistic Real-Time Automata from Multi-Attribute Event Logs
Intelligent Data Analysis Special Issue on Dynak Topics, 7(1):to appear.

Seeland, M, Kramer, S, and Pfahringer, B (2013).
Model Selection Based Product Kernel Learning for Regression on Graphs
In: Proceedings of the 28th Symposium On Applied Computing, pp. 136-143, ACM.

Böck, M, Ogishima, S, Tanaka, H, Kramer, S, and Kaderali, L (2012).
Hub-Centered Gene Network Reconstruction using Automatic Relevance Determination
PLoS ONE, 7(5):e35077.

Duchrow, T, Schröer, M, Griesbach, B, Kasperski, S, Maas genannt Bermpohl, G, Kramer, S, and Kirchner, F (2012).
Towards Electric Mobility Data Mining
In: IEEE International Electric Vehicle Conference (IEVC) 2012, pp. 1-6, IEEE.

Ganzert, S, Kramer, S, and Guttmann, J (2012).
Predicting the lung compliance of mechanically ventilated patients via statistical modeling
Physiological Measurement, 33:345-359.

Geilke, M, Frank, E, and Kramer, S (2012).
Online Estimation of Discrete Densities using Classifier Chains
Miscellaneous publication, ECML-PKDD 2012 workshop Instant Interactive Data Mining.

Grzonka, S, Karwath, A, Dijoux, F, and Burgard, W (2012).
Activity-Based Estimation of Human Trajectories
IEEE Transactions on Robotics, 28(1):234–245.

Gütlein, M, Karwath, A, and Kramer, S (2012).
CheS-Mapper – Chemical Space Mapping and Visualization in 3D
Journal of Cheminformatics, 4(7).

Hapfelmeier, A, Mertes, C, Schmidt, J, and Kramer, S (2012).
Towards Real-Time Machine Learning
In: ECML-PKDD 2012 Workshop: Instant Interactive Data Mining.

Li, R and Kramer, S (2012).
Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming
In: The 15th International Conference on Discovery Science, pp. 125–138, Lyon, France, Springer-Verlag. Lecture Notes in Artificial Intelligence (LNAI).

Pesch, R, Böck, M, and Zimmer, R (2012).
ConReg: Analysis and Visualization of Conserved Regulatory Networks in Eukaryotes
In: Proceedings of the German Conference on Bioinformatics (GCB) 2012, Open Access Series in Informatics of the Schloss Dagstuhl (accepted).

Schmidt, J and Kramer, S (2012).
Online Induction of Probabilistic Real Time Automata
In: Proceedings of the 2012 IEEE International Conference on Data Mining (ICDM 2012).

Schmidt, J, Ansorge, S, and Kramer, S (2012).
Scalable Induction of Probabilistic Real-Time Automata Using Maximum Frequent Pattern Based Clustering
In: Proceedings of the twelfth SIAM International Conference on Data Mining, pp. to appear, SIAM / Omnipress.

Schmidt, J, Hapfelmeier, A, Schmidt, W, and Wollina, U (2012).
Improving Wound Score Classification with Limited Remission Spectra
International Wound Journal, Wiley-Blackwell, 9(2):189-98.

Seeland, M, Karwath, A, and Kramer, S (2012).
A Structural Cluster Kernel for Learning on Graphs
In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 516-524.

Seeland, M, Pfahringer, B, and Kramer, S (2012).
Maximum Common Subgraph Based Locally Weighted Regression
In: Proceedings of the 27th Symposium On Applied Computing, pp. 484-491.

Wicker, J, Pfahringer, B, and Kramer, S (2012).
Multi-Label Classification using Boolean Matrix Decomposition
In: Proceedings of the 27th Symposium On Applied Computing, pp. 498-505, ACM.

Alphonse, E, Girschick, T, Buchwald, F, and Kramer, S (2011).
A Numerical Refinement Operator based on Multi-Instance Learning
In: Inductive Logic Programming - 20th International Conference, ILP 2010, ed. by Paolo Frasconi and Francesca A. Lisi, vol. 6489, pp. 14-21, Springer. LNCS/LNAI.

Buchwald, F, Girschick, T, Seeland, M, and Kramer, S (2011).
Using Local Models to Improve (Q)SAR Predictivity
Molecular Informatics, 30(2-3):205-218.

Buchwald, F, Richter, L, and Kramer, S (2011).
Predicting a small molecule-kinase interaction map: A machine learning approach
Journal of Cheminformatics, 3:22.

Böck, M, Schmitt, C, and Kramer, S (2011).
A Study of Dynamic Time Warping for the Inference of Gene Regulatory Relationships
In: Proceedings of the Fifth International Workshop on Machine Learning in Systems Biology (MLSB11), ed. by S. Kramer and N. Lawrence, pp. 6-9.