activity
20212026
most citedIncentive Compatibility in the Auto-bidding World

2 citations · 4 across the 10 of their papers we have counts for

collaborators

10 papers

cs.SI2026

Auditing the Auditors: Does Community-based Moderation Get It Right?

Yeganeh Alimohammadi, Karissa Huang, Christian Borgs +1

Online social platforms increasingly rely on crowd-sourced systems to label misleading content at scale, but these systems must both aggregate users' evaluations and decide whose e…

stat.ML2025

Mallows Model with Learned Distance Metrics: Sampling and Maximum Likelihood Estimation

Yeganeh Alimohammadi, Kiana Asgari

\textit{Mallows model} is a widely-used probabilistic framework for learning from ranking data, with applications ranging from recommendation systems and voting to aligning languag…

math.PR2025

Local Limits of Small World Networks

Yeganeh Alimohammadi, Senem Işık, Amin Saberi

Small-world networks, known for high local clustering and short path lengths, are a fundamental structure in many real-world systems, including social, biological, and technologica…

cs.LG2023

A Local Graph Limits Perspective on Sampling-Based GNNs

Yeganeh Alimohammadi, Luana Ruiz, Amin Saberi

We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable…

econ.TH2023★ 2 cited

Incentive Compatibility in the Auto-bidding World

Yeganeh Alimohammadi, Aranyak Mehta, Andres Perlroth

Auto-bidding has recently become a popular feature in ad auctions. This feature enables advertisers to simply provide high-level constraints and goals to an automated agent, which…

cs.DS2021

Algorithms Using Local Graph Features to Predict Epidemics

Yeganeh Alimohammadi, Christian Borgs, Amin Saberi

We study a simple model of epidemics where an infected node transmits the infection to its neighbors independently with probability . This is also known as the independent casca…