There are various parametric models for analyzing pairwise comparison data, including the
Bradley-Terry-Luce (BTL) and Thurstone models, but their reliance on strong parametric …

Motivated by its practical success, we show that the 2D total variation denoiser satisfies a
sharp oracle inequality that leads to near optimal rates of estimation for a large class of …

This paper considers inference on fixed effects in a linear regression model estimated from
network data. An important special case of our setup is the two‐way regression model. This …

In this paper, we show that all nodes can be found optimally for almost all random Erdős–
Rényi\mathcal G (n, p) G (n, p) graphs using continuous-time quantum spatial search …

Given a graph where vertices represent alternatives and arcs represent pairwise
comparison data, the statistical ranking problem is to find a potential function, defined on the …

We consider a symmetric mixture of linear regressions with random samples from the
pairwise comparison design, which can be seen as a noisy version of a type of Euclidean …

We study two agent based models of opinion formation—one stochastic in nature and one
deterministic. Both models are defined in terms of an underlying graph; we study how the …

Crowdsourcing platforms are now extensively used for conducting subjective pairwise
comparison studies. In this setting, a pairwise comparison dataset is typically gathered via …

Learning from people represents a new and expanding frontier for data science.
Crowdsourcing, where data is collected from non-experts online, is now extensively …

In recent years, the wealth of available vehicle location data from connected vehicles, cell
phones, and navigation systems has been introduced. This data can be used to improve the …