This paper describes work aimed at the unsupervised learning of shape-classes from shock trees. We commence by considering how to compute the edit distance between weighted trees. ...
Andrea Torsello, Antonio Robles-Kelly, Edwin R. Ha...
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
We introduce Indented Pixel Tree Plots (IPTPs): a novel pixel-based visualization technique for depicting large hierarchies. It is inspired by the visual metaphor of indented outli...
— The Distributed Spanning Tree (DST) is an overlay structure designed to be scalable. It supports the growth from small scale to large scale. The DST is a tree without bottlenec...
Abstract. In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that...