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Thomas Ragg: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Thomas Ragg
    Building Committees by Clustering Models Based on Pairwise Similarity Values. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:406-418 [Conf]
  2. Thomas Ragg, Steffen Gutjahr
    Automatic determination of optimal network topologies based on information theory and evolution. [Citation Graph (0, 0)][DBLP]
    EUROMICRO, 1997, pp:549-555 [Conf]
  3. Thomas Ragg, Martin Granzow, Wolfram Menzel, Werner Dubitzky
    Filtering Nonlinear Intensity Dependencies in cDNA Microarray Experiments. [Citation Graph (0, 0)][DBLP]
    IC-AI, 2003, pp:335-341 [Conf]
  4. Thomas Ragg, Steffen Gutjahr
    Building High Performant Classifiers by Integrating Bayesian Learning, Mutual Information and Committee Techniques - A Case Study in Time Series Prediction. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:1023-1028 [Conf]
  5. Thomas Ragg, Frank Padberg, Ralf Schoknecht
    Applying Machine Learning to Solve an Estimation Problem in Software Inspections. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:516-521 [Conf]
  6. Martin Lauer, Martin A. Riedmiller, Thomas Ragg, Walter Baum, Michael Wigbers
    The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction. [Citation Graph (0, 0)][DBLP]
    IDA, 2003, pp:451-461 [Conf]
  7. Thomas Ragg
    Bayesian Learning and Evolutionary Parameter Optimization. [Citation Graph (0, 0)][DBLP]
    KI/ÖGAI, 2001, pp:48-62 [Conf]
  8. Rainer Malaka, Thomas Ragg, Martin Hammer
    A Model for Chemosensory Reception. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:61-68 [Conf]
  9. Thomas Ragg
    Parallelization of an Evolutionary Neural Network Optimizer Based on PVM. [Citation Graph (0, 0)][DBLP]
    PVM, 1996, pp:351-354 [Conf]
  10. Thomas Ragg
    Bayesian learning and evolutionary parameter optimization. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2002, v:15, n:1, pp:61-74 [Journal]
  11. Thomas Ragg, Wolfram Menzel, Walter Baum, Michael Wigbers
    Bayesian learning for sales rate prediction for thousands of retailers. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:43, n:1-4, pp:127-144 [Journal]
  12. Frank Padberg, Thomas Ragg, Ralf Schoknecht
    Using Machine Learning for Estimating the Defect Content After an Inspection. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Software Eng., 2004, v:30, n:1, pp:17-28 [Journal]

  13. Kinetic models of odor transduction implemented as artificial neural networks. [Citation Graph (, )][DBLP]


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