23 search results - page 2 / 5 » Relative Loss Bounds for Temporal-Difference Learning |
AAAI
1997
13 years 6 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
13 years 8 months 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 6 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 4 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
13 years 9 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...