Duality theories are proposed as a basis for the construction of certain state spaces that appear in Decision Theory. This is considered in more detail in the particular case of Stone Duality. Topological cancellation axioms for preference are introduced. These are used to produce a form of representation for preference between particular acts over state spaces that are Stone spaces. The well-k...

Markov decision processes (MDPs) may involve three types of delays. First, state information, rather than being available instantaneously, may arrive with a delay (observation delay). Second, an action may take effect at a later decision stage rather than immediately (action delay). Third, the cost induced by an action may be collected after a number of stages (cost delay). We derive two result...

In this paper, we provide a thorough analysis of decision boundaries of neural networks when they are used as a classifier. First, we divide the classifying mechanism of the neural network into two parts: dimension expansion by hidden neurons and linear decision boundary formation by output neurons. In this paradigm, the input data is first warped into a higher dimensional space by the hidden n...

In Learning Using Privileged Information (LUPI) paradigm, along with the stan-dard training data in the decision space, a teacher supplies a learner with the priv-ileged information in the correcting space. The goal of the learner is to find aclassifier with a low generalization error in the decision space. We consider anempirical risk minimization algorithm, called Privileged E...

Decision rules that explicitly account for non-probabilistic evaluation metrics in machine translation typically require special training, often to estimate parameters in exponential models that govern the search space and the selection of candidate translations. While the traditional Maximum A Posteriori (MAP) decision rule can be optimized as a piecewise linear function in a greedy search of ...

Decision rules that explicitly account for non-probabilistic evaluation metrics in machine translation typically require special training, often to estimate parameters in exponential models that govern the search space and the selection of candidate translations. While the traditional Maximum A Posteriori (MAP) decision rule can be optimized as a piecewise linear function in a greedy search of ...

This research puts forward rough finite state automata which have been represented by two variants of BDD called ROBDD and ZBDD. The proposed structures have been used in networked system diagnosis and can overcome cominatorial explosion. In implementation the CUDD - Colorado University Decision Diagrams package is used. A mathematical proof for claimed complexity are provided which shows ZBDD ...

Mohammed, North, and Ashton find that decentralization in Fiji shifted health-sector workloads from tertiary hospitals to peripheral health centres, but with little transfer of administrative authority from the centre. Decision-making in five functional areas analysed remains highly centralized. They surmise that the benefits of decentralization in terms of services and outcomes will be limited...

Decentralisation continues to re-appear in health system reform across the world. Evaluation of these reforms reveals how research on decentralisation continues to evolve. In this paper, we examine the theoretical foundations and empirical references which underpin current approaches to studying decentralisation in health systems.