We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditi...
We developed a new hierarchical modular approach for synthesis of area-minimal core-based data-intensive systems. The optimization approach employs a novel global least-constraini...
Spatial objects other than points and boxes can be stored in spatial indexes, but the techniques usually require the use of approximations that can be arbitrarily bad. This leads ...
Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
In this paper, we present a modular co-synthesis framework called CHARMED that solves the problem of hardware-software co-synthesis of periodic, multi-mode, distributed, embedded ...