Phase Transitions and Stochastic Local Search in k-Term DNF Learning. - Ulrich Rückert 002; Stefan Kramer 001; Luc De Raedt (ECML, 2002)

Stochastic Local Search in k-Term DNF Learning. - Ulrich Rückert 002; Stefan Kramer 001 (ICML, 2003)

Generalized Version Space Trees. - Ulrich Rückert 002; Stefan Kramer 001 (KDID, 2003)

Quantitative Association Rules Based on Half-Spaces: An Optimization Approach. - Ulrich Rückert 002; Lothar Richter; Stefan Kramer 001 (ICDM, 2004)

Towards tight bounds for rule learning. - Ulrich Rückert 002; Stefan Kramer 001 (ICML, 2004)

Frequent free tree discovery in graph data. - Ulrich Rückert 002; Stefan Kramer 001 (SAC, 2004)

Analyzing microarray data using quantitative association rules. - Elisabeth Georgii; Lothar Richter; Ulrich Rückert 002; Stefan Kramer 001 (ECCB/JBI, 2005)

A statistical approach to rule learning. - Ulrich Rückert 002; Stefan Kramer 001 (ICML, 2006)

Learning a Predictive Model for Growth Inhibition from the NCI DTP Human Tumor Cell Line Screening Data: Does Gene Expression Make a Difference? - Lothar Richter; Ulrich Rückert 002; Stefan Kramer 001 (Pacific Symposium on Biocomputing, 2006)

Optimizing Feature Sets for Structured Data. - Ulrich Rückert 002; Stefan Kramer 001 (ECML, 2007)

Kernel-Based Inductive Transfer. - Ulrich Rückert 002; Stefan Kramer 001 (ECML/PKDD (2), 2008)

An experimental evaluation of simplicity in rule learning. - Ulrich Rückert 002; Luc De Raedt (Artif. Intell., 2008)

Margin-based first-order rule learning. - Ulrich Rückert 002; Stefan Kramer 001 (Mach. Learn., 2008)

A statistical approach to rule learning. - Ulrich Rückert 002 (2008)

Capacity Control for Partially Ordered Feature Sets. - Ulrich Rückert 002 (ECML/PKDD (2), 2009)

Adaptive concept drift detection. - Anton Dries; Ulrich Rückert 002 (Stat. Anal. Data Min., 2009)

Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships. - Ulrich Rückert 002; Tobias Girschick; Fabian Buchwald; Stefan Kramer 001 (Discovery Science, 2010)

A Unifying View of Multiple Kernel Learning. - Marius Kloft; Ulrich Rückert 002; Peter L. Bartlett (ECML/PKDD (2), 2010)

Fast, Effective Molecular Feature Mining by Local Optimization. - Albrecht Zimmermann; Björn Bringmann; Ulrich Rückert 002 (ECML/PKDD (3), 2010)

Transfer Learning with Adaptive Regularizers. - Ulrich Rückert 002; Marius Kloft (ECML/PKDD (3), 2011)

How Little Do We Actually Know? On the Size of Gene Regulatory Networks. - Richard Röttger; Ulrich Rückert 002; Jan Taubert; Jan Baumbach (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships and Data-Driven Selection of Source Datasets. - Tobias Girschick; Ulrich Rückert 002; Stefan Kramer 001 (Comput. J., 2013)