We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
In this paper we present new and more accurate estimates of the biases of the linear approximation of the FSM of the stream cipher SNOW 2.0. Based on improved bias estimates we als...
The automated analysis of model specifications is an area that historically receives little attention in the simulation research community but which can offer significant bene...
Kara A. Olson, C. Michael Overstreet, E. Joseph De...
In recent years we have resgitered a renewed interest in event detection and temporal processing of text/discourse. TimeML (Pustejovsky et al., 2003a) has shed new lights on the n...