Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
In this paper, the complex-step method is applied in the setting of numerical optimisation problems involving dynamical systems modelled as nonlinear differential equations. The m...
Thispaper describesAPE(the Atlas PlanningEngine),the reactive planner at the center of the Atlas dialogue managementsystem. The goal of Atlas is to build conversation-basedsystems...
We present a method for pipeline verification using SMT solvers. It is based on a non-deterministic “mother pipeline” machine (MOP) that abstracts the instruction set archite...
Implementing an extension of a legacy operating system requires knowing what functionalities the extension should provide and how the extension should be integrated with the legac...
Gilles Muller, Julia L. Lawall, Jean-Marc Menaud, ...