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
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA