Achievability and Impossibility of Exact Pairwise Ranking

11/19/2021
by   Yihan He, et al.
0

We consider the problem of recovering the rank of a set of n items based on noisy pairwise comparisons. We assume the SST class as the family of generative models. Our analysis gave sharp information theoretic upper and lower bound for the exact requirement, which matches exactly in the parametric limit. Our tight analysis on the algorithm induced by the moment method gave better constant in Minimax optimal rate than  <cit.> and contribute to their open problem. The strategy we used in this work to obtain information theoretic bounds is based on combinatorial arguments and is of independent interest.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/30/2015

Simple, Robust and Optimal Ranking from Pairwise Comparisons

We consider data in the form of pairwise comparisons of n items, with th...
research
08/11/2018

Ranking with Features: Algorithm and A Graph Theoretic Analysis

We consider the problem of ranking a set of items from pairwise comparis...
research
02/23/2022

Minimax Optimal Quantization of Linear Models: Information-Theoretic Limits and Efficient Algorithms

We consider the problem of quantizing a linear model learned from measur...
research
02/19/2021

Information-Theoretic Bounds for Integral Estimation

In this paper, we consider a zero-order stochastic oracle model of estim...
research
05/06/2015

Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence

Data in the form of pairwise comparisons arises in many domains, includi...
research
01/28/2016

Information-Theoretic Lower Bounds for Recovery of Diffusion Network Structures

We study the information-theoretic lower bound of the sample complexity ...
research
01/21/2021

Optimal Full Ranking from Pairwise Comparisons

We consider the problem of ranking n players from partial pairwise compa...

Please sign up or login with your details

Forgot password? Click here to reset