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Andrew Skabar: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Andrew Skabar, Kousick Biswas, Binh Pham, Anthony J. Maeder
    Inductive Concept Learning in the Absence of Labeled Counter-Examples. [Citation Graph (0, 0)][DBLP]
    ACSC, 2000, pp:220-226 [Conf]
  2. Andrew Skabar, Ian Cloete
    Neural Networks and Financial Trading and the Efficient Markets Hypothesis. [Citation Graph (0, 0)][DBLP]
    ACSC, 2002, pp:241-249 [Conf]
  3. Andrew Skabar
    Predicting the Distribution of Discrete Spatial Events Using Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2003, pp:567-577 [Conf]
  4. Andrew Skabar
    Single-Class Classification Augmented with Unlabeled Data: A Symbolic Approach. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2003, pp:735-746 [Conf]
  5. Andrew Skabar
    Application of Bayesian Techniques for MLPs to Financial Time Series Forecasting. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2005, pp:888-891 [Conf]
  6. Andrew Skabar
    A GA-based Neural Network Weight Optimization Technique for Semi-Supervised Classifier Learning. [Citation Graph (0, 0)][DBLP]
    HIS, 2003, pp:139-146 [Conf]
  7. Andrew Skabar
    An Objective Function Based on Bayesian Likelihoods of Necessity and Sufficiency For Concept Learning in the Absence of Labeled Counter-Examples. [Citation Graph (0, 0)][DBLP]
    IC-AI, 2004, pp:634-640 [Conf]
  8. Andrew Skabar
    Comparison of MLP and Bayesian Approaches on Mineral Prospectivity Mapping Tasks. [Citation Graph (0, 0)][DBLP]
    IC-AI, 2004, pp:946-952 [Conf]
  9. Andrew Skabar
    Application of Bayesian MLP Techniques to Predicting Mineralization Potential from Geoscientific Data. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:963-968 [Conf]
  10. Andrew Skabar
    Automatic MLP Weight Regularization on Mineralization Prediction Tasks. [Citation Graph (0, 0)][DBLP]
    KES (3), 2005, pp:595-601 [Conf]
  11. Andrew Skabar
    Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data. [Citation Graph (0, 0)][DBLP]
    KI, 2002, pp:174-185 [Conf]
  12. Andrew Skabar, Anthony J. Maeder, Binh Pham
    A Classifier Fitness Measure Based on Bayesian Likelihoods: An Approach to the Problem of Learning from Positives Only. [Citation Graph (0, 0)][DBLP]
    PRICAI, 2000, pp:177-187 [Conf]
  13. Andrew Skabar, Narendra Juneja
    A Kernel-Based Method for Semi-Supervised Learning. [Citation Graph (0, 0)][DBLP]
    ACIS-ICIS, 2007, pp:112-117 [Conf]

  14. A Kernel-Based Technique for Direction-of-Change Financial Time Series Forecasting. [Citation Graph (, )][DBLP]


  15. Lag-Dependent Regularization for MLPs Applied to Financial Time Series Forecasting Tasks. [Citation Graph (, )][DBLP]


  16. Multi-label Classification of Gene Function using MLPs. [Citation Graph (, )][DBLP]


  17. Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents. [Citation Graph (, )][DBLP]


  18. Direction-of-Change Financial Time Series Forecasting Using Neural Networks: A Bayesian Approach. [Citation Graph (, )][DBLP]


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