Noisy Search with Comparative Feedback

UAI 2011 pp. 445-452

/uai/2011/lim2011uai-noisy/

Abstract

We present theoretical results in terms of lower and upper bounds on the query complexity of noisy search with comparative feedback. In this search model, the noise in the feedback depends on the distance between query points and the search target. Consequently, the error probability in the feedback is not fixed but varies for the queries posed by the search algorithm. Our results show that a target out of n items can be found in O(log n) queries. We also show the surprising result that for k possible answers per query, the speedup is not log k (as for k-ary search) but only log log k in some cases.

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Cite

Text

Lim and Auer. "Noisy Search with Comparative Feedback." Conference on Uncertainty in Artificial Intelligence, 2011.

Markdown

[Lim and Auer. "Noisy Search with Comparative Feedback." Conference on Uncertainty in Artificial Intelligence, 2011.](https://mlanthology.org/uai/2011/lim2011uai-noisy/)

BibTeX

@inproceedings{lim2011uai-noisy,
  title     = {{Noisy Search with Comparative Feedback}},
  author    = {Lim, Shiau Hong and Auer, Peter},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {2011},
  pages     = {445-452},
  url       = {https://mlanthology.org/uai/2011/lim2011uai-noisy/}
}