activity
20192026
most citedBayesian Persuasion with Mediators

9 citations · 25 across the 15 of their papers we have counts for

collaborators

17 papers

econ.TH2026

Delegation in Strategic Environments and Equilibrium Uniqueness

Fedor Sandomirskiy, Ben Wincelberg

We ask when a normal-form game yields a single equilibrium prediction, even if players can coordinate by delegating play to an intermediary such as a platform or a cartel. Delegati…

econ.TH2025

Monotonicity and Bracketing in Games

Fedor Sandomirskiy, Po Hyun Sung, Omer Tamuz +1

We study solution concepts for normal-form games. We obtain a characterization of Nash equilibria and logit quantal response equilibria, as well as generalizations capturing non-ex…

econ.TH2024★ 2 cited

The geometry of consumer preference aggregation

Fedor Sandomirskiy, Philip Ushchev

We revisit a classical question of how individual consumer preferences and incomes shape aggregate behavior. We develop a method that applies to populations with homothetic prefere…

econ.TH2024

Stable Matching as Transport: a Welfarist Perspective on Market Design

Federico Echenique, Joseph Root, Fedor Sandomirskiy

This paper links matching markets with aligned preferences to optimal transport theory. We show that stability, efficiency, and fairness emerge as solutions to a parametric family…

econ.TH2023

A Separability Foundation for Random Coefficients Logit

Fedor Sandomirskiy, Po Hyun Sung, Omer Tamuz +1

We study stochastic choice across decision problems, each represented as a menu of action labels paired with observable outcome vectors. We propose a consistency condition for beha…

math.PR2023

On the origin of the Boltzmann distribution

Fedor Sandomirskiy, Omer Tamuz

The family of Boltzmann distributions is used in statistical mechanics to describe the distribution of states in systems with a given temperature. We give a novel characterization…

econ.TH2023

Feasible Conditional Belief Distributions

Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy

Agents receive private signals about an unknown state. The resulting joint belief distributions are complex and lack a simple characterization. Our key insight is that, when condit…

econ.TH2022★ 4 cited

Beckmann's approach to multi-item multi-bidder auctions

Alexander V. Kolesnikov, Fedor Sandomirskiy, Aleh Tsyvinski +1

We consider the problem of revenue-maximizing Bayesian auction design with several bidders having independent private values over several items. We show that it can be reduced to t…

econ.TH2022

Efficiency in Random Resource Allocation and Social Choice

Federico Echenique, Joseph Root, Fedor Sandomirskiy

We study efficiency in general collective choice problems where agents have ordinal preferences and randomization is allowed. We explore the structure of preference profiles where…

econ.TH2022★ 9 cited

Bayesian Persuasion with Mediators

Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy

An informed sender communicates with an uninformed receiver through a sequence of uninformed mediators; agents' utilities depend on receiver's action and the state. For any number…

econ.TH2021★ 1 cited

Private Private Information

Kevin He, Fedor Sandomirskiy, Omer Tamuz

Private signals model noisy information about an unknown state. Although these signals are called "private," they may still carry information about each other. Our paper introduces…

econ.TH2020

On social networks that support learning

Itai Arieli, Fedor Sandomirskiy, Rann Smorodinsky

It is well understood that the structure of a social network is critical to whether or not agents can aggregate information correctly. In this paper, we study social networks that…

cs.GT2020

Representative Committees of Peers

Reshef Meir, Fedor Sandomirskiy, Moshe Tennenholtz

A population of voters must elect representatives among themselves to decide on a sequence of possibly unforeseen binary issues. Voters care only about the final decision, not the…

econ.TH2020

Feasible Joint Posterior Beliefs

Itai Arieli, Yakov Babichenko, Fedor Sandomirskiy +1

We study the set of possible joint posterior belief distributions of a group of agents who share a common prior regarding a binary state, and who observe some information structure…

cs.GT2019★ 9 cited

Efficient Fair Division with Minimal Sharing

Fedor Sandomirskiy, Erel Segal-Halevi

A collection of objects, some of which are good and some are bad, is to be divided fairly among agents with different tastes, modeled by additive utility functions. If the objects…

cs.GT2019

Algorithms for Competitive Division of Chores

Simina Brânzei, Fedor Sandomirskiy

We study the problem of allocating divisible bads (chores) among multiple agents with additive utilities when monetary transfers are not allowed. The competitive rule is known for…

cs.GT2019

Protecting the Protected Group: Circumventing Harmful Fairness

Omer Ben-Porat, Fedor Sandomirskiy, Moshe Tennenholtz

Machine Learning (ML) algorithms shape our lives. Banks use them to determine if we are good borrowers; IT companies delegate them recruitment decisions; police apply ML for crime-…