Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...
We present upper and lower bounds for the number of iterations performed by the Iterative Closest Point (ICP) algorithm. This algorithm has been proposed by Besl and McKay [4] as ...
Practical Recurrent Learning (PRL) has been proposed as a simple learning algorithm for recurrent neural networks[1][2]. This algorithm enables learning with practical order O(n2 )...
Numerous logics have been developed for reasoning about inconsistency which differ in (i) the logic to which they apply, and (ii) the criteria used to draw inferences. In this pap...