Andrew Skabar

According to our database1, Andrew Skabar
  • authored at least 27 papers between 2000 and 2017.
  • has a "Dijkstra number"2 of five.

Timeline

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Bibliography

2017
Clustering Mixed-Attribute Data using Random Walk.
Proceedings of the International Conference on Computational Science, 2017

2016
Random vector generation from mixed-attribute datasets using random walk.
Proceedings of the Winter Simulation Conference, WSC 2016, 2016

2015
Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings Problem.
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015

2013
Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm.
IEEE Trans. Knowl. Data Eng., 2013

2012
Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importance.
TSLP, 2012

2010
Supervised Similarity-Based Classification using a Generative Graph-Based Model.
Austr. J. Intelligent Information Processing Systems, 2010

Density estimation-based document categorization using von Mises-Fisher kernels.
Proceedings of the International Joint Conference on Neural Networks, 2010

Improving Sentence Similarity Measurement by Incorporating Sentential Word Importance.
Proceedings of the AI 2010: Advances in Artificial Intelligence, 2010

Short-Text Similarity Measurement Using Word Sense Disambiguation and Synonym Expansion.
Proceedings of the AI 2010: Advances in Artificial Intelligence, 2010

2009
Lag-Dependent Regularization for MLPs Applied to Financial Time Series Forecasting Tasks.
Proceedings of the Computational Science, 2009

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents.
Proceedings of the Artificial Life: Borrowing from Biology, 4th Australian Conference, 2009

2008
Direction-of-Change Financial Time Series Forecasting Using Neural Networks: A Bayesian Approach.
Proceedings of the Advances in Electrical Engineering and Computational Science, 2008

A Kernel-Based Technique for Direction-of-Change Financial Time Series Forecasting.
Proceedings of the Computational Science, 2008

2007
A Kernel-Based Method for Semi-Supervised Learning.
Proceedings of the 6th Annual IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), 2007

2006
Multi-label Classification of Gene Function using MLPs.
Proceedings of the International Joint Conference on Neural Networks, 2006

2005
Automatic MLP Weight Regularization on Mineralization Prediction Tasks.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2005

Application of Bayesian MLP Techniques to Predicting Mineralization Potential from Geoscientific Data.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Application of Bayesian Techniques for MLPs to Financial Time Series Forecasting.
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005

2004
Comparison of MLP and Bayesian Approaches on Mineral Prospectivity Mapping Tasks.
Proceedings of the International Conference on Artificial Intelligence, 2004

An Objective Function Based on Bayesian Likelihoods of Necessity and Sufficiency For Concept Learning in the Absence of Labeled Counter-Examples.
Proceedings of the International Conference on Artificial Intelligence, 2004

2003
A GA-based Neural Network Weight Optimization Technique for Semi-Supervised Classifier Learning.
Proceedings of the Design and Application of Hybrid Intelligent Systems, 2003

Single-Class Classification Augmented with Unlabeled Data: A Symbolic Approach.
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

Predicting the Distribution of Discrete Spatial Events Using Artificial Neural Networks.
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

2002
Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data.
Proceedings of the KI 2002: Advances in Artificial Intelligence, 2002

Neural Networks and Financial Trading and the Efficient Markets Hypothesis.
Proceedings of the Computer Science 2002, 2002

2000
A Classifier Fitness Measure Based on Bayesian Likelihoods: An Approach to the Problem of Learning from Positives Only.
PRICAI, 2000

Inductive Concept Learning in the Absence of Labeled Counter-Examples.
Proceedings of the 23rd Australasian Computer Science Conference (ACSC 2000), 31 January, 2000


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