Richard Dazeley
Richard Dazeley
Associate Professor, School of Information Technology, Deakin University
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A survey of multi-objective sequential decision-making
DM Roijers, P Vamplew, S Whiteson, R Dazeley
Journal of Artificial Intelligence Research 48, 67-113, 2013
Empirical evaluation methods for multiobjective reinforcement learning algorithms
P Vamplew, R Dazeley, A Berry, R Issabekov, E Dekker
Machine learning 84 (1), 51-80, 2011
Authorship attribution for twitter in 140 characters or less
R Layton, P Watters, R Dazeley
2010 Second Cybercrime and Trustworthy Computing Workshop, 1-8, 2010
On the limitations of scalarisation for multi-objective reinforcement learning of pareto fronts
P Vamplew, J Yearwood, R Dazeley, A Berry
Australasian joint conference on artificial intelligence, 372-378, 2008
Consensus clustering and supervised classification for profiling phishing emails in internet commerce security
R Dazeley, JL Yearwood, BH Kang, AV Kelarev
Pacific Rim Knowledge Acquisition Workshop, 235-246, 2010
Automated unsupervised authorship analysis using evidence accumulation clustering
R Layton, P Watters, R Dazeley
Natural Language Engineering 19 (1), 95, 2013
Automatically determining phishing campaigns using the uscap methodology
R Layton, P Watters, R Dazeley
2010 eCrime Researchers Summit, 1-8, 2010
Human-aligned artificial intelligence is a multiobjective problem
P Vamplew, R Dazeley, C Foale, S Firmin, J Mummery
Ethics and Information Technology 20 (1), 27-40, 2018
Constructing stochastic mixture policies for episodic multiobjective reinforcement learning tasks
P Vamplew, R Dazeley, E Barker, A Kelarev
Australasian joint conference on artificial intelligence, 340-349, 2009
Recentred local profiles for authorship attribution.
R Layton, PA Watters, R Dazeley
Nat. Lang. Eng. 18 (3), 293-312, 2012
A multi-objective deep reinforcement learning framework
TT Nguyen, ND Nguyen, P Vamplew, S Nahavandi, R Dazeley, CP Lim
Engineering Applications of Artificial Intelligence 96, 103915, 2020
Softmax exploration strategies for multiobjective reinforcement learning
P Vamplew, R Dazeley, C Foale
Neurocomputing 263, 74-86, 2017
Steering approaches to Pareto-optimal multiobjective reinforcement learning
P Vamplew, R Issabekov, R Dazeley, C Foale, A Berry, T Moore, ...
Neurocomputing 263, 26-38, 2017
Unsupervised authorship analysis of phishing webpages
R Layton, P Watters, R Dazeley
2012 International Symposium on Communications and Information Technologies …, 2012
Evaluating authorship distance methods using the positive silhouette coefficient
R Layton, P Watters, R Dazeley
Natural Language Engineering 19 (4), 517, 2013
How much material on BitTorrent is infringing content? A case study
PA Watters, R Layton, R Dazeley
Information Security Technical Report 16 (2), 79-87, 2011
Weighted MCRDR: deriving information about relationships between classifications in MCRDR
R Dazeley, BH Kang
Australasian Joint Conference on Artificial Intelligence, 245-255, 2003
Local n-grams for Author Identification
R Layton, P Watters, R Dazeley
Notebook for PAN at CLEF, 2013
Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR.
R Dazeley, BH Kang
IOS Press 104, 499-508, 2003
An online classification and prediction hybrid system for knowledge discovery in databases
R Dazeley, B Kang
University of Tasmania, 2004
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