We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Kernel Miner is a new data-mining tool based on building the optimal decision forest. The tool won second place in the KDD'99 Classifier Learning Contest, August 1999. We des...
We study the proper learnability of axis-parallel concept classes in the PAC-learning and exactlearning models. These classes include union of boxes, DNF, decision trees and multi...
The Kushilevitz-Mansour (KM) algorithm is an algorithm that finds all the “large” Fourier coefficients of a Boolean function. It is the main tool for learning decision trees ...
A concept learning framework for terminological representations is introduced. It is grounded on a method for inducing logic decision trees as an adaptation of the classic tree in...