Abstract. Possibilistic knowledge bases gather propositional formulas associated with degrees belonging to a linearly ordered scale. These degrees reflect certainty or priority, de...
Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
Today many formalisms exist for specifying complex Markov chains. In contrast, formalism for specifying the quantitative properties to analyze have remained quite primitive. In th...
This paper describes a method to optimize the performance of data paths. It is based on bit-level arithmetic transformations, and is especially suited to optimize large adder stru...
Luc Rijnders, Zohair Sahraoui, Paul Six, Hugo De M...
The use of approximation as a method for dealing with complex problems is a fundamental research issue in Knowledge Representation. Using approximation in symbolic AI is not strai...