Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
Constraint Programming is an attractive approach for solving AI planning problems by modelling them as Constraint Satisfaction Problems (CSPs). However, formulating effective cons...
Andrea Rendl, Ian Miguel, Ian P. Gent, Peter Grego...
— Due to continuous technology scaling, the reduction of nodal capacitances and the lowering of power supply voltages result in an ever decreasing minimal charge capable of upset...
Riaz Naseer, Younes Boulghassoul, Jeff Draper, San...
— High-order full-state Markov (FSM) chains have been employed to model errors and losses in many wireless studies. The complexity of this modeling paradigm is an exponential fun...
The quality of the input system model has a direct bearing on the effectiveness of the system exploration and synthesis tools. Given a well-structured system model, tools today are...