Online Submodular Minimization
Journal of Machine Learning Research · 2012 · Volume 13
Abstract
We consider an online decision problem over a discrete space in which the loss function is submodular. We give algorithms which are computationally efficient and are Hannan-consistent in both the full information and partial feedback settings.
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