587 citations · 2.1k across the 58 of their papers we have counts for
7 papers · 1 filter
Simple, Robust and Optimal Ranking from Pairwise Comparisons
Nihar B. Shah, Martin J. Wainwright
We consider data in the form of pairwise comparisons of n items, with the goal of precisely identifying the top k items for some value of k < n, or alternatively, recovering a rank…
Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues
Nihar B. Shah, Sivaraman Balakrishnan, Adityanand Guntuboyina +1
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 ass…
Information-theoretically Secure Erasure Codes for Distributed Storage
Nihar B. Shah, K. V. Rashmi, Kannan Ramchandran +1
Repair operations in distributed storage systems potentially expose the data to malicious acts of passive eavesdroppers or active adversaries, which can be detrimental to the secur…
The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms
Vijay Kamble, Nihar Shah, David Marn +2
A major challenge in obtaining evaluations of products or services on e-commerce platforms is eliciting informative responses in the absence of verifiability. This paper proposes t…
Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence
Nihar B. Shah, Sivaraman Balakrishnan, Joseph Bradley +3
Data in the form of pairwise comparisons arises in many domains, including preference elicitation, sporting competitions, and peer grading among others. We consider parametric ordi…
Regularized Minimax Conditional Entropy for Crowdsourcing
Dengyong Zhou, Qiang Liu, John C. Platt +2
There is a rapidly increasing interest in crowdsourcing for data labeling. By crowdsourcing, a large number of labels can be often quickly gathered at low cost. However, the labels…