Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Abstract. This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of mac...
Mark Schwabacher, Pat Langley, Christopher Potter,...
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
In this paper, we learn the components of dialogue POMDP models from data. In particular, we learn the states, observations, as well as transition and observation functions based o...
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...