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» An Experts Algorithm for Transfer Learning
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ICML
2005
IEEE
14 years 8 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
COLT
2007
Springer
14 years 1 months ago
Regret to the Best vs. Regret to the Average
Abstract. We study online regret minimization algorithms in a bicriteria setting, examining not only the standard notion of regret to the best expert, but also the regret to the av...
Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, ...
COLT
2008
Springer
13 years 9 months ago
Combining Expert Advice Efficiently
We show how models for prediction with expert advice can be defined concisely and clearly using hidden Markov models (HMMs); standard HMM algorithms can then be used to efficientl...
Wouter M. Koolen, Steven de Rooij
ALT
2007
Springer
14 years 1 months ago
Online Regression Competitive with Changing Predictors
This paper deals with the problem of making predictions in the online mode of learning where the dependence of the outcome yt on the signal xt can change with time. The Aggregating...
Steven Busuttil, Yuri Kalnishkan
MLDM
2007
Springer
14 years 1 months ago
Selection of Experts for the Design of Multiple Biometric Systems
Abstract. In the biometric field, different experts are combined to improve the system reliability, as in many application the performance attained by individual experts (i.e., d...
Roberto Tronci, Giorgio Giacinto, Fabio Roli