Simon I. Hill

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These evidence-based guidelines are an updated version of those published in 2006. They have been produced after a literature review of the treatment and prophylaxis of methicillin-resistant Staphylococcus aureus (MRSA). The guidelines aim to complement those recently published for the antibiotic treatment of common and emerging community-onset MRSA(More)
This paper studies three related algorithms: the (traditional) Gradient Descent (GD) Algorithm, the Exponentiated Gradient Algorithm with Positive and Negative weights (EG algorithm) and the Exponentiated Gradient Algorithm with Unnormalized Positive and Negative weights (EGU algorithm). These algorithms have been previously analyzed using the(More)
A geometric framework for understanding multi-category classification is introduced, through which many existing ‘all-together’ algorithms can be understood. The structure enables parsimonious optimisation, through a direct extension of the binary methodology. The focus is on Support Vector Classification, with parallels drawn to related methods. The(More)
Methodologies currently used in load prediction are adapted to study the effect on load demand were the UK to move from GMT to BST (=GMT+1) during winter. In particular Support Vector Regression (SVR) is used to estimate energy demand on a half-hourly basis (given prevailing light and temperature). This resulted in predicted lower bounds on daily savings of(More)
Enclomiphene (Androxal), in development by Repros Therapeutics Inc, is a non-steroidal estrogen receptor antagonist that promotes gonadotropin-dependent testosterone secretion by the testes. Enclomiphene constitutes the trans-stereoisomer of clomiphene citrate, a drug that has been widely prescribed for several decades for the treatment of female ovulatory(More)
A geometric construction is presented which is shown to be an effective tool for understanding and implementing multi-category support vector classification. It is demonstrated how this construction can be used to extend many other existing two-class kernel-based classification methodologies in a straightforward way while still preserving attractive(More)
In this paper, the perceptually based loss functions for audio filtering used by Wolfe and Godsill [1] are shown to fit well within a complex-valued Support Vector Machine (SVM) framework. SVM regression is extended to estimation of complex-valued functions, including the derivation of a variant of the Sequential Minimal Optimisation (SMO) algorithm. Audio(More)
In this paper we study the problem of generalisation in information retrieval. In particular we study precision-recall curves and the average precision value. We provide two types of bounds: large-deviation bounds of the average precision and maximum deviation bounds with respect to a given point of the precision recall curve. The rst type of bounds are(More)
We propose a system that can reliably track multiple cars in congested traffic environments. Our system's key basis is the implementation of a sequential Monte Carlo algorithm, which introduces robustness against problems arising due to the proximity between vehicles. By directly modelling occlusions and collisions between cars we obtain promising results(More)