This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
The current evaluation functions for heuristic planning are expensive to compute. In numerous domains these functions give good guidance on the solution, so it worths the computat...
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
Wireless sensor networks are tightly associated with the underlying environment in which the sensors are deployed. The global topology of the network is of great importance to bot...
— Genetic algorithms (GAs) have been argued to constitute a flexible search thereby enabling to solve difficult problems which classical optimization methodologies may find ha...
Jose M. Cabello, Jose M. Cejudo, Mariano Luque, Fr...