| 2004 |
|---|
| 12 | EE | Frank Padberg,
Thomas Ragg,
Ralf Schoknecht:
Using Machine Learning for Estimating the Defect Content After an Inspection.
IEEE Trans. Software Eng. 30(1): 17-28 (2004) |
| 2003 |
|---|
| 11 | | Thomas Ragg,
Martin Granzow,
Wolfram Menzel,
Werner Dubitzky:
Filtering Nonlinear Intensity Dependencies in cDNA Microarray Experiments.
IC-AI 2003: 335-341 |
| 10 | EE | Martin Lauer,
Martin A. Riedmiller,
Thomas Ragg,
Walter Baum,
Michael Wigbers:
The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction.
IDA 2003: 451-461 |
| 2002 |
|---|
| 9 | EE | Thomas Ragg,
Frank Padberg,
Ralf Schoknecht:
Applying Machine Learning to Solve an Estimation Problem in Software Inspections.
ICANN 2002: 516-521 |
| 8 | EE | Thomas Ragg:
Bayesian learning and evolutionary parameter optimization.
AI Commun. 15(1): 61-74 (2002) |
| 7 | EE | Thomas Ragg,
Wolfram Menzel,
Walter Baum,
Michael Wigbers:
Bayesian learning for sales rate prediction for thousands of retailers.
Neurocomputing 43(1-4): 127-144 (2002) |
| 2001 |
|---|
| 6 | EE | Thomas Ragg:
Building Committees by Clustering Models Based on Pairwise Similarity Values.
ECML 2001: 406-418 |
| 5 | EE | Thomas Ragg:
Bayesian Learning and Evolutionary Parameter Optimization.
KI/ÖGAI 2001: 48-62 |
| 1997 |
|---|
| 4 | EE | Thomas Ragg,
Steffen Gutjahr:
Automatic determination of optimal network topologies based on information theory and evolution.
EUROMICRO 1997: 549-555 |
| 3 | | Thomas Ragg,
Steffen Gutjahr:
Building High Performant Classifiers by Integrating Bayesian Learning, Mutual Information and Committee Techniques - A Case Study in Time Series Prediction.
ICANN 1997: 1023-1028 |
| 1996 |
|---|
| 2 | | Thomas Ragg:
Parallelization of an Evolutionary Neural Network Optimizer Based on PVM.
PVM 1996: 351-354 |
| 1994 |
|---|
| 1 | EE | Rainer Malaka,
Thomas Ragg,
Martin Hammer:
A Model for Chemosensory Reception.
NIPS 1994: 61-68 |
