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Streaming Adaptive Submodular Maximization

Artificial Intelligence 2022-08-18 v1 Machine Learning

Abstract

Many sequential decision making problems can be formulated as an adaptive submodular maximization problem. However, most of existing studies in this field focus on pool-based setting, where one can pick items in any order, and there have been few studies for the stream-based setting where items arrive in an arbitrary order and one must immediately decide whether to select an item or not upon its arrival. In this paper, we introduce a new class of utility functions, semi-policywise submodular functions. We develop a series of effective algorithms to maximize a semi-policywise submodular function under the stream-based setting.

Keywords

Cite

@article{arxiv.2208.08021,
  title  = {Streaming Adaptive Submodular Maximization},
  author = {Shaojie Tang and Jing Yuan},
  journal= {arXiv preprint arXiv:2208.08021},
  year   = {2022}
}

Comments

This paper has been accepted at The 16th International Conference on Algorithmic Aspects in Information and Management (AAIM 2022)