Abstract:
Suppose that we are able to obtain binary paired comparisons of the form “x is closer to p than to q” for various choices of vectors p and q. Such observations arise in a...Show MoreMetadata
Abstract:
Suppose that we are able to obtain binary paired comparisons of the form “x is closer to p than to q” for various choices of vectors p and q. Such observations arise in a variety of contexts, including nonmetric multidimensional scaling, unfolding, and ranking problems, often because they provide a powerful and flexible model of preference. In this paper we give a theoretical bound for how well we can expect to estimate x under a randomized model for p and q. We also show that we can achieve significant gains by adaptively changing the distribution for choosing p and q.
Published in: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 05-09 March 2017
Date Added to IEEE Xplore: 19 June 2017
ISBN Information:
Electronic ISSN: 2379-190X