In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
Recently, due to its wide applications, subgraph search has attracted a lot of attention from database and data mining community. Sub-graph search is defined as follows: given a ...
Today biometric techniques are based either on passive (e.g. IrisScan, Face) or active methods (e.g. voice and handwriting). In our work we focus on evaluation of the latter. These...
Franziska Wolf, T. K. Basu, Pranab K. Dutta, Claus...
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...