← Search

Alexandros Psomas

13 accepted papers

2025

Mechanism Design via the Interim Relaxation

NeurIPS 2025poster

We study revenue maximization for agents with additive preferences, subject to downward-closed constraints on the set of feasible allocations. In seminal work,~\citet{alaei2014bayesian} introduced a powerful multi-to-single agent reduction based on an ex-ante relaxation of the multi-agent problem. T…

Cited by 0SourceScholar
2025

On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness

NeurIPS 2025poster

We consider the classic cake-cutting problem of producing fair allocations for $n$ agents, in the Robertson–Webb query model. In this model, it is known that: (i) proportional allocations can be computed using $O(n \log n)$ queries, and this is optimal for deterministic protocols; (ii) envy-free all…

Cited by 0SourceScholar
2024

Getting More by Knowing Less: Bayesian Incentive Compatible Mechanisms for Fair Division

IJCAI 2024poster

We study fair resource allocation with strategic agents. It is well-known that, across multiple fundamental problems in this domain, truthfulness and fairness are incompatible. For example, when allocating indivisible goods, no truthful and deterministic mechanism can guarantee envy-freeness up to o…

Cited by 3SourcePDFScholar
2023

On the Robustness of Mechanism Design under Total Variation Distance

NeurIPS 2023poster

We study the problem of designing mechanisms when agents' valuation functions are drawn from unknown and correlated prior distributions. In particular, we are given a prior distribution $D$, and we are interested in designing a (truthful) mechanism that has good performance for all "true distributio…

Cited by 6SourcePDFScholar
2023

Refined Mechanism Design for Approximately Structured Priors via Active Regression

NeurIPS 2023poster

We consider the problem of a revenue-maximizing seller with a large number of items $m$ for sale to $n$ strategic bidders, whose valuations are drawn independently from high-dimensional, unknown prior distributions. It is well-known that optimal and even approximately-optimal mechanisms for this set…

Cited by 0SourcePDFScholar
2022

On Infinite Separations Between Simple and Optimal Mechanisms

NeurIPS 2022accept

We consider a revenue-maximizing seller with $k$ heterogeneous items for sale to a single additive buyer, whose values are drawn from a known, possibly correlated prior $\mathcal{D}$. It is known that there exist priors $\mathcal{D}$ such that simple mechanisms --- those with bounded menu complexity…

Cited by 5SourcePDFScholar
2022

Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions

NeurIPS 2022accept

Internet ad auctions have evolved from a few lines of text to richer informational layouts that include images, sitelinks, videos, etc. Ads in these new formats occupy varying amounts of space, and an advertiser can provide multiple formats, only one of which can be shown. The seller is now faced wi…

Cited by 5SourcePDFScholar
2021

Fair and Efficient Online Allocations with Normalized Valuations

AAAI 2021technical

A set of divisible resources becomes available over a sequence of rounds and needs to be allocated immediately and irrevocably. Our goal is to distribute these resources to maximize fairness and efficiency. Achieving any non-trivial guarantees in an adversarial setting is impossible. However, we sho…

Cited by 25SourcePDFScholar
2020

Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics

NeurIPS 2020spotlight

We consider the fundamental problem of selecting $k$ out of $n$ random variables in a way that the expected highest or second-highest value is maximized. This question captures several applications where we have uncertainty about the quality of candidates (e.g. auction bids, search results) and have…

Cited by 17SourcePDFScholar