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» Relative Loss Bounds for Temporal-Difference Learning
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145
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AAAI
1997
15 years 7 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
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 ...
Tom Bylander
COLT
2006
Springer
15 years 9 months ago
Online Multitask Learning
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 ...
Ofer Dekel, Philip M. Long, Yoram Singer
138
Voted
NIPS
2003
15 years 7 months ago
Online Learning of Non-stationary Sequences
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...
Claire Monteleoni, Tommi Jaakkola
AI
1998
Springer
15 years 5 months ago
Worst-Case Analysis of the Perceptron and Exponentiated Update Algorithms
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...
Tom Bylander
216
Voted
EUROCOLT
1999
Springer
15 years 10 months ago
Averaging Expert Predictions
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...
Jyrki Kivinen, Manfred K. Warmuth