Min-Max Submodular Ranking for Multiple Agents
نویسندگان
چکیده
In the submodular ranking (SR) problem, input consists of a set functions defined on ground elements. The goal is to order elements for all have value above certain threshold as soon average possible, assuming we choose one element per time. problem flexible enough capture various applications in machine learning, including decision trees. This paper considers min-max version SR where multiple instances share set. With view each instance being associated with an agent, common minimize maximum objective agents---thus, finding fair solution agents. We give approximation algorithms this and demonstrate their effectiveness application tree
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i6.25862