We study the problem of approximating pseudoBoolean functions by linear pseudo-Boolean functions. Pseudo-Boolean functions generalize ordinary Boolean functions by allowing the fu...
Guoli Ding, Robert F. Lax, Peter P. Chen, Jianhua ...
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
The selection of valuable features is crucial in pattern recognition. In this paper we deal with the issue that part of features originate from directional instead of common linea...
Abstract. Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling,...
lem of inferring termination from such abstract information is not the halting problem for programs and may well be decidable. If this is the case, the decision algorithm forms a &...