We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
Evidence from recent psycholinguistic experiments suggests that humans resolve reference incrementally in the presence of constraining visual context. In this paper, we present an...
Matthias Scheutz, Kathleen M. Eberhard, Virgil And...
Constraint satisfaction has been applied with great success in closed-world scenarios, where all options and constraints are known from the beginning and fixed. With the internet,...
—Constraints allow users to declare relationships among objects and let the constraint systems maintain and satisfy these relationships. Formulas have been adopted to express con...
Kai Lin, David Chen, R. Geoff Dromey, Chengzheng S...
Constraining and input biasing are frequently used techniques in functional verification methodologies based on randomized simulation generation. Constraints confine the simulatio...
Jun Yuan, Kurt Shultz, Carl Pixley, Hillel Miller,...