We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms ...
Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, ...
This paper analyzes the notion of a minimal belief change that incorporates new information. I apply the fundamental decisiontheoretic principle of Pareto-optimality to derive a no...
When working with diagrams in visual environments like graphical diagram editors, diagrams have to be represented by an internal model. Graphs and hypergraphs are well-known concep...
This paper investigates an extension of classification trees to deal with uncertain information where uncertainty is encoded in possibility theory framework. Class labels in data s...
Ilyes Jenhani, Nahla Ben Amor, Salem Benferhat, Zi...
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...