23 search results - page 2 / 5 » Relative Loss Bounds for Temporal-Difference Learning |
AAAI
1997
13 years 10 months ago
1997
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
COLT
2006
Springer
14 years 15 days ago
2006
Springer
We study the problem of online learning of multiple tasks in parallel. On each online round, the algorithm receives an instance and makes a prediction for each one of the parallel ...
NIPS
2003
13 years 10 months ago
2003
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a cla...
AI
1998
Springer
13 years 8 months ago
1998
Springer
The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worst-case upper bounds on the absolute loss for the Perceptron le...
EUROCOLT
1999
Springer
14 years 1 months ago
1999
Springer
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...