Andrew Skabar - researchr alias

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Viewing Publication 1 - 28 from 28

2019

Restricted Boltzmann Machines: an Eigencentrality-based ApproachAndrew Skabar. ijcnn 2019: 1-8 [doi]

2017

Clustering Mixed-Attribute Data using Random WalkAndrew Skabar. iccs 2017: 988-997 [doi]

2016

Random vector generation from mixed-attribute datasets using random walkAndrew Skabar. wsc 2016: 1096-1107 [doi]

2015

Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings ProblemAlphan Culha, Andrew Skabar. ausai 2015: 136-148 [doi]

2013

Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering AlgorithmAndrew Skabar, Khaled Abdalgader. tkde, 25(1):62-75, 2013. [doi]

2012

Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importanceKhaled Abdalgader, Andrew Skabar. tslp, 9(1):2, 2012. [doi]

2010

Short-Text Similarity Measurement Using Word Sense Disambiguation and Synonym ExpansionKhaled Abdalgader, Andrew Skabar. ausai 2011: 435-444 [doi]

Density estimation-based document categorization using von Mises-Fisher kernelsAndrew Skabar, Shahmeer Memon. ijcnn 2010: 1-8 [doi]

Supervised Similarity-Based Classification using a Generative Graph-Based ModelAndrew Skabar. ajiips, 12(3), 2010. [doi]

Improving Sentence Similarity Measurement by Incorporating Sentential Word ImportanceAndrew Skabar, Khaled Abdalgader. ausai 2011: 466-475 [doi]

2009

Evolutionary Intelligence and Communication in Societies of Virtually Embodied AgentsBinh Nguyen, Andrew Skabar. ACAL 2009: 73-85 [doi]

Lag-Dependent Regularization for MLPs Applied to Financial Time Series Forecasting TasksAndrew Skabar. iccS 2009: 515-523 [doi]

2008

A Kernel-Based Technique for Direction-of-Change Financial Time Series ForecastingAndrew Skabar. iccS 2008: 441-449 [doi]

Direction-of-Change Financial Time Series Forecasting Using Neural Networks: A Bayesian ApproachAndrew Skabar. wce 2009: 515-524 [doi]

2007

A Kernel-Based Method for Semi-Supervised LearningAndrew Skabar, Narendra Juneja. ACISicis 2007: 112-117 [doi]

2006

Multi-label Classification of Gene Function using MLPsAndrew Skabar, Dennis Wollersheim, Tim Whitfort. ijcnn 2006: 2234-2240 [doi]

2005

Automatic MLP Weight Regularization on Mineralization Prediction TasksAndrew Skabar. kes 2005: 595-601 [doi]

Application of Bayesian MLP Techniques to Predicting Mineralization Potential from Geoscientific DataAndrew Skabar. icann 2005: 963-968 [doi]

Application of Bayesian Techniques for MLPs to Financial Time Series ForecastingAndrew Skabar. ausai 2005: 888-891 [doi]

2004

An Objective Function Based on Bayesian Likelihoods of Necessity and Sufficiency For Concept Learning in the Absence of Labeled Counter-ExamplesAndrew Skabar. icai 2004: 634-640

Comparison of MLP and Bayesian Approaches on Mineral Prospectivity Mapping TasksAndrew Skabar. icai 2004: 946-952

2003

A GA-based Neural Network Weight Optimization Technique for Semi-Supervised Classifier LearningAndrew Skabar. his 2003: 139-146

Single-Class Classification Augmented with Unlabeled Data: A Symbolic ApproachAndrew Skabar. ausai 2003: 735-746 [doi]

Predicting the Distribution of Discrete Spatial Events Using Artificial Neural NetworksAndrew Skabar. ausai 2003: 567-577 [doi]

2002

Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled DataAndrew Skabar. ki 2002: 174-185 [doi]

Neural Networks and Financial Trading and the Efficient Markets HypothesisAndrew Skabar, Ian Cloete. acsc 2002: 241-249 [doi]

2000

Inductive Concept Learning in the Absence of Labeled Counter-ExamplesAndrew Skabar, Kousick Biswas, Binh Pham, Anthony J. Maeder. acsc 2000: 220-226 [doi]

A Classifier Fitness Measure Based on Bayesian Likelihoods: An Approach to the Problem of Learning from Positives OnlyAndrew Skabar, Anthony J. Maeder, Binh Pham. pricai 2000: 177-187

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