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Date: 2015
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/155260
Description: Missing values may be present in data without undermining its use for diagnostic / classification purposes but compromise application of readily available software. Surrogate entries can remedy the si... More
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Date: 2014
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/76602
Description: Impact of water quality conditions in sources on the optimal operation of a regional multiquality water distribution system is analysed. Three operational objectives are concurrently minimised, being ... More
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Date: 2011
Type: Conference proceedings
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/45743
Description: Dimensionality reduction of the problem space through detection and removal of variables, contributing little or not at all to classification, is able to relieve the computational load and instance ac... More
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Date: 2010
Type: Conference paper
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/58789
Description: Abstract Water resource development has played a crucial role in the Grampians, Wimmera and Mallee regions of Australia, with the main source of surface water located in several reservoirs in the Gram... More
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Date: 2010
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/64179
Description: An L-2-boosting algorithm for estimation of a regression function from random design is presented, which consists of fitting repeatedly a function from a fixed nonlinear function space to the residual... More
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Date: 2010
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/31612
Description: Naive Bayes classifier is the simplest among Bayesian Network classifiers. It has shown to be very efficient on a variety of data classification problems. However, the strong assumption that all featu... More
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Date: 2009
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/31920
Description: In this paper, estimation of a regression function from independent and identically distributed random variables is considered. Estimates are defined by minimization of the empirical L2 risk over a cl... More
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Date: 2008
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/42339
Description: The problem of the estimation of a regression function by continuous piecewise linear functions is formulated as a nonconvex, nonsmooth optimization problem. Estimates are defined by minimization of t... More
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Date: 2008
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/64682
Description: In this paper a new algorithm for minimizing locally Lipschitz functions is developed. Descent directions in this algorithm are computed by solving a system of linear inequalities. The convergence of ... More
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Date: 2008
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/41954
Description: A new derivative-free method is developed for solving unconstrained nonsmooth optimization problems. This method is based on the notion of a discrete gradient. It is demonstrated that the discrete gra... More
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Authors: Bagirov, Adil
Date: 2008
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/38401
Description: k-Means algorithm and its variations are known to be fast clustering algorithms. However, they are sensitive to the choice of starting points and inefficient for solving clustering problems in large d... More
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Date: 2007
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/37635
Description: In this paper the problem of localization of wireless sensor network is formulated as an unconstrained nonsmooth optimization problem. We minimize a distance objective function which incorporates unkn... More
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Date: 2007
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/57012
Description: Many optimization problems related to integrated oil and gas production systems are nonconvex and multimodal. Additionally, apart from the innate nonsmoothness of many optimization problems, nonsmooth... More
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Date: 2007
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/58118
Description: The relatively new field of stream mining has necessitated the development of robust drift-aware algorithms that provide accurate, real time, data handling capabilities. Tools are needed to assess and... More
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Date: 2006
Type: Text
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/46175
Description: Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a few algorithms can be... More
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