Many machine learning tasks contain feature evaluation as one of its important components. This work is concerned with attribute estimation in the problems where class distribution...
We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries...
Dana Angluin, David Eisenstat, Leonid Kontorovich,...
Abstract. This exposition paper suggests a new low-bandwidth publickey encryption paradigm. The construction turns a weak form of key privacy into message privacy as follows: let E...
Symbolic universal planning based on the reduced Ordered Binary Decision Diagram (OBDD) has been shown to be an efficient approach for planning in non-deterministic domains. To d...
Rune M. Jensen, Manuela M. Veloso, Randal E. Bryan...