In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
The rapid increase in the data volumes for the past few decades has intensified the need for high processing power for database and data mining applications. Researchers have acti...
Anastassia Ailamaki, Naga K. Govindaraju, Dinesh M...
We investigate the management of flocking mobile objects using a parallel message-passing computer cluster. An octree, a data structure well-known for use in managing a 3D space, ...
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...