5938b4d054136e5d59ada6ec9c295d7a-Paper.pdf

Neural Information Processing Systems 

The widely studiedGeneralized Min-Sum-Set-Cover(GMSSC) problem serves as a formal model for the setting above. GMSSC is NP-hard and the standard application ofno-regretonline learning algorithms iscomputationally inefficient, because they operate in the space of rankings. In this work, we show how to achievelowregret for GMSSC inpolynomial-time.

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