Quantile Search with Time-Varying Search Parameter

Authors

John Lipor, Portland State UniversityFollow
Gautam Dasarathy, Arizona State University

Published In

2018 52nd Asilomar Conference on Signals, Systems, and Computers

Document Type

Citation

Publication Date

2-21-2019

Abstract

We consider the problem of active learning in the context of spatial sampling, where the sampling cost is a function of both the number of samples taken and the distance traveled during the sampling procedure. We present Uniform-to-Binary (UTB) search, a novel algorithm in this setting. UTB search extends the Quantile Search (QS) algorithm [1] such that the tuning parameter m is allowed to vary throughout the search procedure. We analyze the algorithm in terms of both sample complexity and distance traveled. Empirical results show that our proposed method outperforms QS with fixed m in all cases considered.

Description

© Copyright 2019 IEEE - All rights reserved.

Locate the Document

http://dx.doi.org/10.1109/ACSSC.2018.8645332

DOI

10.1109/ACSSC.2018.8645332

Persistent Identifier

https://archives.pdx.edu/ds/psu/29049

Citation Details

J. Lipor and G. Dasarathy, "Quantile Search with Time-Varying Search Parameter," 2018 52nd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2018, pp. 1016-1018.