Sequence Selection by Pareto Optimization

@inproceedings{Qian2018SequenceSB,
  title={Sequence Selection by Pareto Optimization},
  author={Chao Qian and Chao Feng and Ke Tang},
  booktitle={IJCAI},
  year={2018}
}
  • Chao Qian, Chao Feng, Ke Tang
  • Published in IJCAI 2018
  • Computer Science
  • The problem of selecting a sequence of items from a universe that maximizes some given objective function arises in many real-world applications. In this paper, we propose an anytime randomized iterative approach POSEQSEL, which maximizes the given objective function and minimizes the sequence length simultaneously. We prove that for any previously studied objective function, POSEQSEL using a reasonable time can always reach or improve the best known approximation guarantee. Empirical results… CONTINUE READING

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