We propose a refinement approach to language emptiness, which is based on the enumeration and the successive refinements of SCCs on over-approximations of the exact system. Our alg...
Chao Wang, Roderick Bloem, Gary D. Hachtel, Kavita...
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Abstract. Recently, the variational Bayesian approximation was applied to probabilistic matrix factorization and shown to perform very well in experiments. However, its good perfor...
There exist many tools for capturing imprecision in probabilistic representations. Among them are random sets, possibility distributions, probability intervals, and the more recen...
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...