An Efficient Streaming Algorithm for the Submodular Cover Problem
November 25, 2016 Β· Declared Dead Β· π Neural Information Processing Systems
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Authors
Ashkan Norouzi-Fard, Abbas Bazzi, Marwa El Halabi, Ilija Bogunovic, Ya-Ping Hsieh, Volkan Cevher
arXiv ID
1611.08574
Category
cs.DS: Data Structures & Algorithms
Citations
22
Venue
Neural Information Processing Systems
Last Checked
3 months ago
Abstract
We initiate the study of the classical Submodular Cover (SC) problem in the data streaming model which we refer to as the Streaming Submodular Cover (SSC). We show that any single pass streaming algorithm using sublinear memory in the size of the stream will fail to provide any non-trivial approximation guarantees for SSC. Hence, we consider a relaxed version of SSC, where we only seek to find a partial cover. We design the first Efficient bicriteria Submodular Cover Streaming (ESC-Streaming) algorithm for this problem, and provide theoretical guarantees for its performance supported by numerical evidence. Our algorithm finds solutions that are competitive with the near-optimal offline greedy algorithm despite requiring only a single pass over the data stream. In our numerical experiments, we evaluate the performance of ESC-Streaming on active set selection and large-scale graph cover problems.
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