We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
We propose and evaluate QuWi (Quality in Wikipedia), a framework for quality control in Wikipedia. We build upon a previous proposal by Mizzaro [11], who proposed a method for sub...
Alberto Cusinato, Vincenzo Della Mea, Francesco Di...
Much of the information on the Web is found in articles from online news outlets, magazines, encyclopedias, review collections, and other sources. However, extracting this content...
This paper presents a general framework for building classifiers that deal with short and sparse text & Web segments by making the most of hidden topics discovered from larges...