We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss func...
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Expert finding addresses the problem of retrieving a ranked list of people who are knowledgeable on a given topic. Several models have been proposed to solve this task, but so far...
Local experts have been used to great effect for fitting deformable
models to images. Typically, the best location in
an image for the deformable model’s landmarks are found
t...
When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of complexity/current loss renders the analys...