Andrew Skabar

According to our database, Andrew Skabar authored at least 29 papers between 2000 and 2019.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2019

Restricted Boltzmann Machines: an Eigencentrality-based Approach.

Andrew Skabar

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications.

Andrew Skabar

CoRR, 2018

2017

Clustering Mixed-Attribute Data using Random Walk.

Andrew Skabar

Proceedings of the International Conference on Computational Science, 2017

2016

Random vector generation from mixed-attribute datasets using random walk.

Andrew Skabar

Proceedings of the Winter Simulation Conference, 2016

2015

Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings Problem.

Alphan Culha, Andrew Skabar

Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015

2013

Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm.

Andrew Skabar, Khaled Abdalgader

IEEE Trans. Knowl. Data Eng., 2013

2012

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

Khaled Abdalgader, Andrew Skabar

ACM Trans. Speech Lang. Process., 2012

2010

Supervised Similarity-Based Classification using a Generative Graph-Based Model.

Andrew Skabar

Aust. J. Intell. Inf. Process. Syst., 2010

Density estimation-based document categorization using von Mises-Fisher kernels.

Andrew Skabar, Shahmeer Memon

Proceedings of the International Joint Conference on Neural Networks, 2010

Improving Sentence Similarity Measurement by Incorporating Sentential Word Importance.

Andrew Skabar, Khaled Abdalgader

Proceedings of the AI 2010: Advances in Artificial Intelligence, 2010

Short-Text Similarity Measurement Using Word Sense Disambiguation and Synonym Expansion.

Khaled Abdalgader, Andrew Skabar

Proceedings of the AI 2010: Advances in Artificial Intelligence, 2010

2009

Lag-Dependent Regularization for MLPs Applied to Financial Time Series Forecasting Tasks.

Andrew Skabar

Proceedings of the Computational Science, 2009

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents.

Binh Nguyen, Andrew Skabar

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.

Andrew Skabar

Proceedings of the Advances in Electrical Engineering and Computational Science, 2008

A Kernel-Based Technique for Direction-of-Change Financial Time Series Forecasting.

Andrew Skabar

Proceedings of the Computational Science, 2008

2007

A Kernel-Based Method for Semi-Supervised Learning.

Andrew Skabar, Narendra Juneja

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.

Andrew Skabar, Dennis Wollersheim, Tim Whitfort

Proceedings of the International Joint Conference on Neural Networks, 2006

2005

Automatic MLP Weight Regularization on Mineralization Prediction Tasks.

Andrew Skabar

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2005

Application of Bayesian MLP Techniques to Predicting Mineralization Potential from Geoscientific Data.

Andrew Skabar

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Application of Bayesian Techniques for MLPs to Financial Time Series Forecasting.

Andrew Skabar

Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005

2004

Comparison of MLP and Bayesian Approaches on Mineral Prospectivity Mapping Tasks.

Andrew Skabar

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.

Andrew Skabar

Proceedings of the International Conference on Artificial Intelligence, 2004

2003

A GA-based Neural Network Weight Optimization Technique for Semi-Supervised Classifier Learning.

Andrew Skabar

Proceedings of the Design and Application of Hybrid Intelligent Systems, 2003

Single-Class Classification Augmented with Unlabeled Data: A Symbolic Approach.

Andrew Skabar

Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

Predicting the Distribution of Discrete Spatial Events Using Artificial Neural Networks.

Andrew Skabar

Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

2002

Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data.

Andrew Skabar

Proceedings of the KI 2002: Advances in Artificial Intelligence, 2002

Neural Networks and Financial Trading and the Efficient Markets Hypothesis.

Andrew Skabar, Ian Cloete

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.

Andrew Skabar, Anthony J. Maeder, Binh Pham

Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000

Inductive Concept Learning in the Absence of Labeled Counter-Examples.

Andrew Skabar, Kousick Biswas, Binh Pham, Anthony J. Maeder

Proceedings of the 23rd Australasian Computer Science Conference (ACSC 2000), 31 January, 2000