This paper demonstrates how machine learning methods can be applied to deal with a realworld decipherment problem where very little background knowledge is available. The goal is ...
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulati...
Jun Sun, Wenbo Zhao, Jiangwei Xue, Zhiyong Shen, Y...
There has been some ambiguity about the growth of attractors in Kauffman networks with network size. Some recent work has linked this to the role and growth of circuits or loops o...
Abstract. We describe a method for enumerating all essentially different executions possible for a cryptographic protocol. We call them the shapes of the protocol. Naturally occur...
Shaddin F. Doghmi, Joshua D. Guttman, F. Javier Th...