We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
In modern databases, complex objects like multimedia data, proteins or text objects can be modeled in a variety of representations and can be decomposed into multiple instances of ...
Stefan Brecheisen, Hans-Peter Kriegel, Matthias Sc...
We introduce quotient graphs for modeling neutrality in evolutionary search. We demonstrate that for a variety of evolutionary computing problems, search can be characterized by g...
Using local features with nearest neighbor search and direct voting obtains excellent results for various image classification tasks. In this work we decompose the method into its...
Daniel Keysers, Hermann Ney, Roberto Paredes, Tobi...
In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a bla...
David Biliotti, Gianluca Antonini, Jean-Philippe T...