Andrew Skabar

Publication Activity (10 Years)

Years Active: 2000-2019
Publications (10 Years): 5

Top Topics

Semi Supervised

Sense Disambiguation

Collaborative Filtering

Top Venues

ACM Trans. Speech Lang. Process.

Australasian Conference on Artificial Intelligence

Publications

Andrew Skabar
Restricted Boltzmann Machines: an Eigencentrality-based Approach. IJCNN (2019)
Andrew Skabar
Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications. CoRR (2018)
Andrew Skabar
Clustering Mixed-Attribute Data using Random Walk. ICCS (2017)
Andrew Skabar
Random vector generation from mixed-attribute datasets using random walk. WSC (2016)
Alphan Culha, Andrew Skabar
Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings Problem. Australasian Conference on Artificial Intelligence (2015)
Andrew Skabar, Khaled Abdalgader
Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm. IEEE Trans. Knowl. Data Eng. 25 (1) (2013)
Khaled Abdalgader, Andrew Skabar
Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importance. ACM Trans. Speech Lang. Process. 9 (1) (2012)
Khaled Abdalgader, Andrew Skabar
Short-Text Similarity Measurement Using Word Sense Disambiguation and Synonym Expansion. Australasian Conference on Artificial Intelligence (2010)
Andrew Skabar, Khaled Abdalgader
Improving Sentence Similarity Measurement by Incorporating Sentential Word Importance. Australasian Conference on Artificial Intelligence (2010)
Andrew Skabar
Supervised Similarity-Based Classification using a Generative Graph-Based Model. Aust. J. Intell. Inf. Process. Syst. 12 (3) (2010)
Andrew Skabar, Shahmeer Memon
Density estimation-based document categorization using von Mises-Fisher kernels. IJCNN (2010)
Binh Nguyen, Andrew Skabar
Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents. ACAL (2009)
Andrew Skabar
Lag-Dependent Regularization for MLPs Applied to Financial Time Series Forecasting Tasks. ICCS (2) (2009)
Andrew Skabar
A Kernel-Based Technique for Direction-of-Change Financial Time Series Forecasting. ICCS (2) (2008)
Andrew Skabar
Direction-of-Change Financial Time Series Forecasting Using Neural Networks: A Bayesian Approach. World Congress on Engineering (Selected Papers) (2008)
Andrew Skabar, Narendra Juneja
A Kernel-Based Method for Semi-Supervised Learning. ACIS-ICIS (2007)
Andrew Skabar, Dennis Wollersheim, Tim Whitfort
Multi-label Classification of Gene Function using MLPs. IJCNN (2006)
Andrew Skabar
Application of Bayesian MLP Techniques to Predicting Mineralization Potential from Geoscientific Data. ICANN (2) (2005)
Andrew Skabar
Application of Bayesian Techniques for MLPs to Financial Time Series Forecasting. Australian Conference on Artificial Intelligence (2005)
Andrew Skabar
Automatic MLP Weight Regularization on Mineralization Prediction Tasks. KES (3) (2005)
Andrew Skabar
An Objective Function Based on Bayesian Likelihoods of Necessity and Sufficiency For Concept Learning in the Absence of Labeled Counter-Examples. IC-AI (2004)
Andrew Skabar
Comparison of MLP and Bayesian Approaches on Mineral Prospectivity Mapping Tasks. IC-AI (2004)
Andrew Skabar
Predicting the Distribution of Discrete Spatial Events Using Artificial Neural Networks. Australian Conference on Artificial Intelligence (2003)
Andrew Skabar
A GA-based Neural Network Weight Optimization Technique for Semi-Supervised Classifier Learning. HIS (2003)
Andrew Skabar
Single-Class Classification Augmented with Unlabeled Data: A Symbolic Approach. Australian Conference on Artificial Intelligence (2003)
Andrew Skabar, Ian Cloete
Neural Networks and Financial Trading and the Efficient Markets Hypothesis. ACSC (2002)
Andrew Skabar
Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data. KI (2002)
Andrew Skabar, Kousick Biswas, Binh Pham, Anthony J. Maeder
Inductive Concept Learning in the Absence of Labeled Counter-Examples. ACSC (2000)
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. PRICAI (2000)