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, ...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest” of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach co...
Recent advances in LiDAR (Light Detection and Ranging) technology have allowed for the remote sensing of important forest characteristics to be more reliable and commercially avail...
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
Many recent applications deal with data streams, conceptually endless sequences of data records, often arriving at high flow rates. Standard data-mining techniques typically assu...
Hanady Abdulsalam, David B. Skillicorn, Patrick Ma...