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» Evolution with Drifting Targets
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ICML
2005
IEEE
15 years 10 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
2010
Springer
14 years 7 months ago
Regret Minimization With Concept Drift
In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jenni...
ICIP
2009
IEEE
14 years 7 months ago
Multichannel dual domain infrared target tracking for highly evolutionary target signatures
We introduce a new SIR particle filter that performs tracking in a joint feature space where pixel domain data are fused with measurements obtained from an 18-channel modulation d...
Colin M. Johnston, Nick A. Mould, Joseph P. Havlic...
ASSETS
2008
ACM
14 years 11 months ago
Hover or tap?: supporting pen-based menu navigation for older adults
Tablet PCs are gaining popularity, but many users, particularly older ones, still struggle with pen-based interaction. One type of error, drifting, occurs when users accidentally ...
Karyn Moffatt, Sandra Yuen, Joanna McGrenere
ECCV
2010
Springer
15 years 2 months ago
A Stochastic Graph Evolution Framework for Robust Multi-Target Tracking
Maintaining the stability of tracks on multiple targets in video over extended time periods remains a challenging problem. A few methods which have recently shown encouraging resul...