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 ...
In recent years realistic input models for geometric algorithms have been studied. The most important models introduced are fatness, low density, unclutteredness, and small simple...
Mark de Berg, Haggai David, Matthew J. Katz, Mark ...
Managing the execution of scientific applications in a heterogeneous grid computing environment can be a daunting task, particularly for long running jobs. Increasing fault tolera...
We study two packing problems that arise in the area of dissemination-based information systems; a second theme is the study of distributed approximation algorithms. The problems c...
—We present an empirical usability experiment studying the relative strengths and weaknesses of three different occlusion management techniques for discovering and accessing obje...