Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the features. In some cases, there is a test cost constraint due to limited resources. We shall deliberately select an informative and cheap feature subset for classification. This paper proposes the featu...

The complexity of any optimisation problem depends critically on the form of the objective function. Valued constraint satisfaction problems are discrete optimisation problems where the function to be minimised is given as a sum of cost functions defined on specified subsets of variables. These cost functions are chosen from some fixed set of available cost functions, known as a valued constrai...

Cost-based abduction attempts to prove an observation by assuming some set of hypotheses. Hypotheses have associated cost and the best proof is the one which assumes the least costly set. Previous approaches have formalized minimum cost-based abduction as a heuristic search problem. However, eecient admissible heuristics seem to be diicult to nd. In this paper, we present an approach using line...

The complexity of any optimisation problem depends critically on the form of the objective function. Valued constraint satisfaction problems are discrete optimisation problems where the function to be minimised is given as a sum of cost functions defined on specified subsets of variables. These cost functions are chosen from some fixed set of available cost functions, known as a valued constrai...

Optimizing the manufacturing cost is critical in tolerance synthesis. Decreasing the tolerance range will improve performance but will also increase the manufacturing costs. It is desirable to optimize the tolerance range under such constraints of product design as the relationship between the dimensions of entities of a component and the functional requirement of the design. We propose a const...