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EUROCOLT
1999
Springer
13 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
COLT
2006
Springer
13 years 10 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
AI
1998
Springer
13 years 6 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
NIPS
2003
13 years 7 months ago
Online Passive-Aggressive Algorithms
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...
NIPS
2003
13 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