We introduce a new collaborative machine learning paradigm in which the user directs a learning algorithm by manually editing the automatically induced model. We identify a generi...
Vittorio Castelli, Lawrence D. Bergman, Daniel Obl...
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
When translating among languages that differ substantially in word order, machine translation (MT) systems benefit from syntactic preordering—an approach that uses features fro...
In this work, a new type of collaborative learning activity is proposed in order to enable students to explore and understand information in highly mobile situations. We call this ...
Gustavo Zurita, Nelson Baloian, Pedro Antunes, Fel...