An optimization query asks for one or more data objects that maximize or minimize some function over the data set. We propose a general class of queries, model-based optimization ...
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...
Abstract. It is well-known that Abstract State Machines (ASMs) can simulate “stepby-step” any type of machines (Turing machines, RAMs, etc.). We aim to overcome two facts: 1) s...
In this paper, a novel learning based method is proposed for No-Reference image quality assessment. Instead of examining the exact prior knowledge for the given type of distortion...
we propose a repository to characterize OO evolution problematic. The two main objectives are to characterize object evolution according to its own features, and to uniformly analy...