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@INPROCEEDINGS{kveton2010online,
  author = {Branislav Kveton and Michal Valko and Matthai Phillipose and Ling
	Huang},
  title = {Online Semi-Supervised Perception: Real-Time Learning without Explicit
	Feedback},
  booktitle = {The Fourth IEEE Online Learning for Computer Vision Workshop in The
	Twenty--Third IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2010},
  address = {San Francisco, CA},
  abstract = {This paper proposes an algorithm for real-time learning without explicit
	feedback. The algorithm combines the ideas of semi-supervised learning
	on graphs and online learning. In particular, it iteratively builds
	a graphical representation of its world and updates it with observed
	examples. Labeled examples constitute the initial bias of the algorithm
	and are provided offline, and a stream of unlabeled examples is collected
	online to update this bias. We motivate the algorithm, discuss how
	to implement it efficiently, prove a regret bound on the quality
	of its solutions, and apply it to the problem of real-time face recognition.
	Our recognizer runs in real time, and achieves superior precision
	and recall on 3 challenging video datasets.},
  owner = {misovalko},
  timestamp = {2010.06.06}
}