Abstract. This paper considers the dynamic tree (DT) model, first introduced in [1]. A dynamic tree specifies a prior over structures of trees, each of which is a forest of one or ...
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
Abstract. Finding an image’s exact GPS location is a challenging computer vision problem that has many real-world applications. In this paper, we address the problem of finding ...
In this paper, a hybrid learning approach named HDT is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to d...
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...