Tom Howley

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The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classification of data. One problem that faces the user of an SVM is how to choose a kernel and the specific parameters for that kernel. Applications of an SVM therefore require a search for the optimum settings for a particular problem. This paper proposes a(More)
This paper describes an extension to reinforcement learning (RL), in which a standard RL algorithm is augmented with a mechanism for transferring experience gained in one problem to new but related problems. In this approach, named Progressive RL, an agent acquires experience of operating in a simple environment through experimentation, and then engages in(More)
The classification of high dimensional data, such as images, gene-expression data and spectral data, poses an interesting challenge to machine learning , as the presence of high numbers of redundant or highly correlated attributes can seriously degrade classification accuracy. This paper investigates the use of Principal Component Analysis (PCA) to reduce(More)
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