Lifted inference, handling whole sets of indistinguishable objects together, is critical to the effective application of probabilistic relational models to realistic real world ta...
Kristian Kersting, Youssef El Massaoudi, Fabian Ha...
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
We present algorithms based on truth-prefixed tableaux to solve both Concept Abduction and Contraction in ALN DL. We also analyze the computational complexity of the problems, sho...
Simona Colucci, Tommaso Di Noia, Eugenio Di Sciasc...
Volume rendering techniques can be very useful in geographical information systems to provide meaningful and visual information about the surface and the interior of 3D datasets. ...