The Thematic Programme will foster research on learning models and algorithms when - in contrast to supervised learning - information about the correct predictions are not immediately available to the learner. The assumption of full information about a training instance is often unrealistic and in many applications the learner must deal with limited feedback. Although some aspects of learning with limited feedback have already been thoroughly analyzed (e.g., multi-armed bandit problems), many problems are still open.
Partial or Delayed Feedback
June 2009 - ongoing
Organiser: Peter Auer (firstname.lastname@example.org)
Among others the following topics are relevant for this Thematic Programme:
The Thematic Programme will start in June 2009.
- Reinforcement learning as a model of delayed feedback, where the utility of predictions/actions might be revealed only after a number of further predictions.
- Variants of the bandit problem as models of partial feedback, where only the utility of the learner's predictions is available but not the utility of possible alternative predictions.
- Models of indirect feedback, where neither the true outcome nor the utility of the prediction is observed, but only an indirect feedback loosely related to the prediction.
- In general, the exploration-exploitation trade-off in learning models.
- Semi-supervised and active learning.
If you are interested in participating in the programme by organizing a workshop, a challenge or in any other way, please contact the organiser. If your workshop or other activity fits into the Thematic Programme, it is eligible for higher level of PASCAL funding and it is more likely to be funded at all.
Events and activities of the Thematic Programme: