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2000 – 2009
- 2004
[j4]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
- [c12]Thomas Ragg, Martin Granzow, Wolfram Menzel, Werner Dubitzky:
Filtering Nonlinear Intensity Dependencies in cDNA Microarray Experiments. IC-AI 2003: 335-341 - [c11]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
- [j3]Thomas Ragg:
Bayesian learning and evolutionary parameter optimization. AI Commun. 15(1): 61-74 (2002) - [j2]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) - [c10]Thomas Ragg, Frank Padberg, Ralf Schoknecht:
Applying Machine Learning to Solve an Estimation Problem in Software Inspections. ICANN 2002: 516-521 - 2001
- [c9]Thomas Ragg:
Building Committees by Clustering Models Based on Pairwise Similarity Values. ECML 2001: 406-418 - [c8]Thomas Ragg:
Bayesian Learning and Evolutionary Parameter Optimization. KI/ÖGAI 2001: 48-62 - 2000
- [b1]Thomas Ragg:
Problemlösung durch Komitees neuronaler Netze. Karlsruhe Institute of Technology, Germany, 2000
1990 – 1999
- 1997
- [c7]Thomas Ragg, Steffen Gutjahr:
Automatic determination of optimal network topologies based on information theory and evolution. EUROMICRO 1997: 549-555 - [c6]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 - [c5]Thomas Ragg, Heinrich Braun, Heiko Landsberg:
A Comparative Study of Neural Network Optimization Techniques. ICANNGA 1997: 341-345 - [c4]Heinrich Braun, Thomas Ragg:
Evolutionary Optimization of Neural Networks for Reinforcement Learning Algorithms. ICANNGA 1997: 384-388 - 1996
- [c3]Dominik Hörnel, Thomas Ragg:
Learning Musical Structure and Style by Recognition, Prediction and Evolution. ICMC 1996 - [c2]Thomas Ragg:
Parallelization of an Evolutionary Neural Network Optimizer Based on PVM. PVM 1996: 351-354 - 1995
- [j1]Rainer Malaka, Thomas Ragg, Martin Hammer:
Kinetic models of odor transduction implemented as artificial neural networks. Biol. Cybern. 73(3): 195-207 (1995) - 1994
- [c1]Rainer Malaka, Thomas Ragg, Martin Hammer:
A Model for Chemosensory Reception. NIPS 1994: 61-68
Coauthor Index
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