activity
20182026
most citedNaive Bayesian Learning in Social Networks

8 citations · 16 across the 11 of their papers we have counts for

collaborators

12 papers

cs.DS2026

Trading with the STARS: Algorithm Design & Spectrum of Fundamental Limits for Trading with Storage

Jerry Anunrojwong, Akshit Kumar, Rachitesh Kumar

We study an online trading problem where a trader, given a sequence of i.i.d. prices drawn from a known distribution on , must make irrevocable buy, sell, or hold decisi…

econ.TH2026

Robust Scale-Free Auctions

Jerry Anunrojwong

We study prior-independent auction design when bidder values are independently and identically distributed and the seller knows only a scale-invariant shape restriction on their di…

eess.SY2026

Residential Battery Pooling Under Backup Commitments

Jerry Anunrojwong, Baosen Zhang

Residential batteries increasingly serve two roles: they can earn money by arbitraging wholesale prices and providing grid services, and they provide backup power during outages. T…

econ.TH2024

Battery Operations in Electricity Markets: Strategic Behavior and Distortions

Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes +1

Battery storage can reduce electricity generation costs by shifting energy across time, but as privately owned batteries become large, they may also be able to exert market power.…

math.OC2024

The Best of Many Robustness Criteria in Decision Making: Formulation and Application to Robust Pricing

Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes

In robust decision-making under non-Bayesian uncertainty, different robust optimization criteria, such as maximin performance, minimax regret, and maximin ratio, have been proposed…

econ.TH2023★ 1 cited

Robust Auction Design with Support Information

Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes

A seller wants to sell an item to buyers. Buyer valuations are drawn i.i.d. from a distribution unknown to the seller; the seller only knows that the support is included in $[a…

econ.TH2022

Persuading Risk-Conscious Agents: A Geometric Approach

Jerry Anunrojwong, Krishnamurthy Iyer, David Lingenbrink

We consider a persuasion problem between a sender and a receiver whose utility may be nonlinear in her belief; we call such receivers risk-conscious. Such utility models arise when…

econ.TH2022★ 2 cited

On the Robustness of Second-Price Auctions in Prior-Independent Mechanism Design

Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes

Classical Bayesian mechanism design relies on the common prior assumption, but such prior is often not available in practice. We study the design of prior-independent mechanisms th…

econ.TH2022★ 2 cited

Social Learning under Platform Influence: Consensus and Persistent Disagreement

Ozan Candogan, Nicole Immorlica, Bar Light +1

Individuals increasingly rely on social networking platforms to form opinions. However, these platforms typically aim to maximize engagement, which may not align with social good.…

cs.GT2020★ 3 cited

Computing Equilibria of Prediction Markets via Persuasion

Jerry Anunrojwong, Yiling Chen, Bo Waggoner +1

We study the computation of equilibria in prediction markets in perhaps the most fundamental special case with two players and three trading opportunities. To do so, we show equiva…

cs.GT2020

Information Design for Congested Social Services: Optimal Need-Based Persuasion

Jerry Anunrojwong, Krishnamurthy Iyer, Vahideh Manshadi

We study the effectiveness of information design in reducing congestion in social services catering to users with varied levels of need. In the absence of price discrimination and…

cs.SI2018★ 8 cited

Naive Bayesian Learning in Social Networks

Jerry Anunrojwong, Nat Sothanaphan

The DeGroot model of naive social learning assumes that agents only communicate scalar opinions. In practice, agents communicate not only their opinions, but their confidence in su…