We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
As part of a large effort to acquire large repositories of facts from unstructured text on the Web, a seed-based framework for textual information extraction allows for weakly sup...
Score normalization is indispensable in distributed retrieval and fusion or meta-search where merging of result-lists is required. Distributional approaches to score normalization...
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
The increasingly common practice of replicating datasets and using resources as distributed data stores in Grid environments has led to the problem of determining which replica ca...