This paper deals with the localization of multiple sources from two-channel mixtures recorded in a reverberant environment. We introduce new angular spectrum-based methods relying...
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
Context-free grammars cannot be identified in the limit from positive examples (Gold, 1967), yet natural language grammars are more powerful than context-free grammars and humans ...
Tim Oates, Tom Armstrong, Justin Harris, Mark Nejm...
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...