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 introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or ...
Using multiple independent networks (also known as rails) is an emerging technique to overcome bandwidth limitations and enhance fault tolerance of current high-performance parall...
Salvador Coll, Eitan Frachtenberg, Fabrizio Petrin...
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
We study the branching program complexity of the tree evaluation problem, introduced in [BCM+09a] as a candidate for separating NL from LogCFL. The input to the problem is a roote...
Mark Braverman, Stephen A. Cook, Pierre McKenzie, ...