PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Online submodular minimization for combinatorial structures
Stefanie Jegelka and Jeff Bilmes
In: ICML 2011, 28 June - 02 July, Bellevue, USA.


Most results for online decision problems with structured concepts, such as trees or cuts, assume linear costs. In many settings, however, nonlinear costs are more realistic. Owing to their non-separability, these lead to much harder optimization problems. Going beyond linearity, we address online approximation algorithms for structured concepts that allow the cost to be submodular, i.e., nonseparable. In particular, we show regret bounds for three Hannan-consistent strategies that capture different settings. Our results also tighten a regret bound for unconstrained online submodular minimization.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:8779
Deposited By:Stefanie Jegelka
Deposited On:21 February 2012