This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
The complexity, variation, and change of human languages makes evident the importance of representation and learning in the acquisition and evolution of language. For example, anal...
Yoosook Lee, Travis C. Collier, Gregory M. Kobele,...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...