2008 |
59 | EE | Ulrich Rückert,
Stefan Kramer:
Kernel-Based Inductive Transfer.
ECML/PKDD (2) 2008: 220-233 |
58 | EE | Jörg Wicker,
Lothar Richter,
Kristina Kessler,
Stefan Kramer:
SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model.
ECML/PKDD (2) 2008: 690-694 |
57 | EE | Lothar Richter,
Jörg Wicker,
Kristina Kessler,
Stefan Kramer:
An inductive database and query language in the relational model.
EDBT 2008: 740-744 |
56 | EE | Andreas Hapfelmeier,
Jana Schmidt,
Marianne Mueller,
Stefan Kramer,
Robert Perneczky,
Alexander Kurz,
Alexander Drzezga:
Interpreting PET Scans by Structured Patient Data: A Data Mining Case Study in Dementia Research.
ICDM 2008: 213-222 |
55 | EE | Kathrin Fenner,
Junfeng Gao,
Stefan Kramer,
Lynda B. M. Ellis,
Lawrence P. Wackett:
Data-driven extraction of relative reasoning rules to limit combinatorial explosion in biodegradation pathway prediction.
Bioinformatics 24(18): 2079-2085 (2008) |
54 | EE | Ulrich Rückert,
Stefan Kramer:
Margin-based first-order rule learning.
Machine Learning 70(2-3): 189-206 (2008) |
53 | EE | Sebastian Fröhler,
Stefan Kramer:
Inductive logic programming for gene regulation prediction.
Machine Learning 70(2-3): 225-240 (2008) |
2007 |
52 | EE | Ulrich Rückert,
Stefan Kramer:
Optimizing Feature Sets for Structured Data.
ECML 2007: 716-723 |
2006 |
51 | | Lothar Richter,
Stefan Hechtl,
Stefan Kramer:
Leveraging Chemical Background Knowledge for the Prediction of Growth Inhibition.
BIBE 2006: 319-324 |
50 | EE | Ulrich Rückert,
Stefan Kramer:
A statistical approach to rule learning.
ICML 2006: 785-792 |
49 | EE | Sebastian Fröhler,
Stefan Kramer:
Inductive Logic Programming for Gene Regulation Prediction.
ILP 2006: 34-36 |
48 | EE | Ulrich Rückert,
Stefan Kramer:
Margin-Based First-Order Rule Learning.
ILP 2006: 46-48 |
47 | EE | Johannes Fischer,
Volker Heun,
Stefan Kramer:
Optimal String Mining Under Frequency Constraints.
PKDD 2006: 139-150 |
46 | EE | Lothar Richter,
Ulrich Rückert,
Stefan Kramer:
Learning a Predictive Model for Growth Inhibition from the NCI DTP Human Tumor Cell Line Screening Data: Does Gene Expression Make a Difference?
Pacific Symposium on Biocomputing 2006: 596-607 |
45 | EE | Fabian Birzele,
Stefan Kramer:
A new representation for protein secondary structure prediction based on frequent patterns.
Bioinformatics 22(21): 2628-2634 (2006) |
44 | EE | Hendrik Blockeel,
David Jensen,
Stefan Kramer:
Introduction to the special issue on multi-relational data mining and statistical relational learning.
Machine Learning 62(1-2): 3-5 (2006) |
2005 |
43 | | Stefan Kramer,
Bernhard Pfahringer:
Inductive Logic Programming, 15th International Conference, ILP 2005, Bonn, Germany, August 10-13, 2005, Proceedings
Springer 2005 |
42 | EE | Elisabeth Georgii,
Lothar Richter,
Ulrich Rückert,
Stefan Kramer:
Analyzing microarray data using quantitative association rules.
ECCB/JBI 2005: 129 |
41 | EE | Johannes Fischer,
Volker Heun,
Stefan Kramer:
Fast Frequent String Mining Using Suffix Arrays.
ICDM 2005: 609-612 |
40 | EE | Vahan Harput,
Hermann Kaindl,
Stefan Kramer:
Extending Function Point Analysis of Object-Oriented Requirements Specifications.
IEEE METRICS 2005: 39 |
39 | EE | Stefan Kramer,
Volker Aufschild,
Andreas Hapfelmeier,
Alexander Jarasch,
Kristina Kessler,
Stefan Reckow,
Jörg Wicker,
Lothar Richter:
Inductive Databases in the Relational Model: The Data as the Bridge.
KDID 2005: 124-138 |
38 | EE | Lin Dong,
Eibe Frank,
Stefan Kramer:
Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
PKDD 2005: 84-95 |
2004 |
37 | EE | Ulrich Rückert,
Lothar Richter,
Stefan Kramer:
Quantitative Association Rules Based on Half-Spaces: An Optimization Approach.
ICDM 2004: 507-510 |
36 | EE | Eibe Frank,
Stefan Kramer:
Ensembles of nested dichotomies for multi-class problems.
ICML 2004 |
35 | EE | Ulrich Rückert,
Stefan Kramer:
Towards tight bounds for rule learning.
ICML 2004 |
34 | EE | Ulrich Rückert,
Stefan Kramer:
Frequent free tree discovery in graph data.
SAC 2004: 564-570 |
33 | EE | Stefan Kramer,
Hermann Kaindl:
Coupling and cohesion metrics for knowledge-based systems using frames and rules.
ACM Trans. Softw. Eng. Methodol. 13(3): 332-358 (2004) |
32 | EE | Hendrik Blockeel,
Saso Dzeroski,
Boris Kompare,
Stefan Kramer,
Bernhard Pfahringer,
Wim Van Laer:
Experiments In Predicting Biodegradability.
Applied Artificial Intelligence 18(2): 157-181 (2004) |
31 | EE | Christoph Helma,
Tobias Cramer,
Stefan Kramer,
Luc De Raedt:
Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds.
Journal of Chemical Information and Modeling 44(4): 1402-1411 (2004) |
2003 |
30 | EE | Hermann Kaindl,
Stefan Kramer,
Mario Hailing,
Vahan Harput:
Metamodel-Compliance Checking of Requirements in a Semiformal Representation.
CAiSE Short Paper Proceedings 2003 |
29 | | Ulrich Rückert,
Stefan Kramer:
Stochastic Local Search in k-Term DNF Learning.
ICML 2003: 648-655 |
28 | | Ulrich Rückert,
Stefan Kramer:
Generalized Version Space Trees.
KDID 2003: 119-129 |
27 | EE | Kristian Kersting,
Tapani Raiko,
Stefan Kramer,
Luc De Raedt:
Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models.
Pacific Symposium on Biocomputing 2003: 192-203 |
26 | | Christoph Helma,
Stefan Kramer:
A Survey of the Predictive Toxicology Challenge 2000-2001.
Bioinformatics 19(10): 1179-1182 (2003) |
25 | | Hannu Toivonen,
Ashwin Srinivasan,
Ross D. King,
Stefan Kramer,
Christoph Helma:
Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001.
Bioinformatics 19(10): 1183-1193 (2003) |
2002 |
24 | EE | Ulrich Rückert,
Stefan Kramer,
Luc De Raedt:
Phase Transitions and Stochastic Local Search in k-Term DNF Learning.
ECML 2002: 405-417 |
23 | | Björn Bringmann,
Stefan Kramer,
Friedrich Neubarth,
Hannes Pirker,
Gerhard Widmer:
Transformation-Based Regression.
ICML 2002: 59-66 |
22 | | Steven Ganzert,
Josef Guttmann,
Kristian Kersting,
Ralf Kuhlen,
Christian Putensen,
Michael Sydow,
Stefan Kramer:
Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning.
Artificial Intelligence in Medicine 26(1-2): 69-86 (2002) |
2001 |
21 | | Stefan Kramer,
Luc De Raedt:
Feature Construction with Version Spaces for Biochemical Applications.
ICML 2001: 258-265 |
20 | | Luc De Raedt,
Stefan Kramer:
The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding.
IJCAI 2001: 853-862 |
19 | EE | Stefan Kramer:
Demand-Driven Construction of Structural Features in ILP.
ILP 2001: 132-141 |
18 | EE | Stefan Kramer,
Luc De Raedt,
Christoph Helma:
Molecular feature mining in HIV data.
KDD 2001: 136-143 |
17 | | Christoph Helma,
Ross D. King,
Stefan Kramer,
Ashwin Srinivasan:
The Predictive Toxicology Challenge 2000-2001.
Bioinformatics 17(1): 107-108 (2001) |
16 | | Stefan Kramer,
Gerhard Widmer,
Bernhard Pfahringer,
Michael de Groeve:
Prediction of Ordinal Classes Using Regression Trees.
Fundam. Inform. 47(1-2): 1-13 (2001) |
2000 |
15 | | Johannes Fürnkranz,
Bernhard Pfahringer,
Hermann Kaindl,
Stefan Kramer:
Learning to Use Operational Advice.
ECAI 2000: 291-295 |
14 | EE | Stefan Kramer,
Eibe Frank:
Bottom-Up Propositionalization.
ILP Work-in-progress reports 2000 |
13 | EE | Stefan Kramer,
Gerhard Widmer,
Bernhard Pfahringer,
Michael de Groeve:
Prediction of Ordinal Classes Using Regression Trees.
ISMIS 2000: 426-434 |
12 | | Stefan Kramer:
Thesis: Relational learning vs. propositionalization.
AI Commun. 13(4): 275-276 (2000) |
1999 |
11 | EE | Hermann Kaindl,
Stefan Kramer,
Papa Samba Niang Diallo:
Semiautomatic Generation of Glossary Links: A Practical Solution.
Hypertext 1999: 3-12 |
10 | EE | Saso Dzeroski,
Hendrik Blockeel,
Boris Kompare,
Stefan Kramer,
Bernhard Pfahringer,
Wim Van Laer:
Experiments in Predicting Biodegradability.
ILP 1999: 80-91 |
1998 |
9 | EE | Hermann Kaindl,
Stefan Kramer,
Luis Miguel Afonso:
Combining Structure Search and Content Search for the World-Wide Web.
Hypertext 1998: 217-224 |
8 | EE | Hermann Kaindl,
Stefan Kramer,
Robert Kacsich:
A Case Study of Decomposing Functional Requirements Using Scenarios.
ICRE 1998: 156-163 |
7 | | Stefan Kramer,
Bernhard Pfahringer,
Christopher Helma:
Stochastic Propositionalization of Non-determinate Background Knowledge.
ILP 1998: 80-94 |
1997 |
6 | EE | Christoph Welsch,
Alexander Schalk,
Stefan Kramer:
Integrating Forward and Reverse Object-Oriented Software Engineering.
ICSE 1997: 560-561 |
5 | | Stefan Kramer,
Hermann Kaindl,
Stefan Schlee:
Can We Benefit from Metrics in KBS Development?
IJCAI (1) 1997: 662-667 |
4 | | Stefan Kramer,
Bernhard Pfahringer,
Christoph Helma:
Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail.
KDD 1997: 223-226 |
1996 |
3 | | Stefan Kramer:
Structural Regression Trees.
AAAI/IAAI, Vol. 1 1996: 812-819 |
2 | | Stefan Kramer,
Bernhard Pfahringer:
Efficient Search for Strong Partial Determinations.
KDD 1996: 371-374 |
1995 |
1 | | Bernhard Pfahringer,
Stefan Kramer:
Compression-Based Evaluation of Partial Determinations.
KDD 1995: 234-239 |