In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is s...
Kun Deng, Chris Bourke, Stephen D. Scott, Julie Su...
Experimental methodology for evaluating classification algorithms in relational (i.e., networked) data is complicated by dependencies between related data instances. We survey the...
An integrated, reconfigurable, adaptable and open system for mining, indexing and retrieving multimedia information based on a mobile agent technology scheme is presented. The sys...
Nikolaos Papadakis, Anastasios D. Doulamis, Dimitr...
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...