Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
This paper addresses the problem of similar image retrieval, especially in the setting of large-scale datasets with millions to billions of images. The core novel contribution is ...
Users’ search needs are often represented by words and images are retrieved according to such textual queries. Annotation words assigned to the stored images are most useful to ...
During the last decade national archives, libraries, museums and companies started to make their records, books and files electronically available. In order to allow efficient ac...
Andreas Stoffel, David Spretke, Henrik Kinnemann, ...