Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Sharing huge, massively distributed databases in P2P systems is inherently difficult. As the amount of stored data increases, data localization techniques become no longer suffi...
Rabab Hayek, Guillaume Raschia, Patrick Valduriez,...
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...
We explore a stacked framework for learning to predict dependency structures for natural language sentences. A typical approach in graph-based dependency parsing has been to assum...
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...