The aim of this paper is to survey and brie y discuss various rules of conditioning proposed in the framework of possibility theory as well as various conditional independence rel...
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
We consider sums of functions of subtrees of a random binary search tree, and obtain general laws of large numbers and central limit theorems. These sums correspond to random recur...
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast ...
— We consider perfect secret key generation for a “pairwise independent network” model in which every pair of terminals share a random binary string, with the strings shared ...