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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]