English

Sequential Preference-Based Optimization

Machine Learning 2018-01-10 v1 Computational Engineering, Finance, and Science Human-Computer Interaction Machine Learning

Abstract

Many real-world engineering problems rely on human preferences to guide their design and optimization. We present PrefOpt, an open source package to simplify sequential optimization tasks that incorporate human preference feedback. Our approach extends an existing latent variable model for binary preferences to allow for observations of equivalent preference from users.

Keywords

Cite

@article{arxiv.1801.02788,
  title  = {Sequential Preference-Based Optimization},
  author = {Ian Dewancker and Jakob Bauer and Michael McCourt},
  journal= {arXiv preprint arXiv:1801.02788},
  year   = {2018}
}