Demo Data from EDBT 2026 / reviewers in the wild / expert
Matthew vonAllmen
dblp:371/4929
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0003-4753-5504ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Approximation and online algorithms · 44% Algorithmic game theory and mechanism design · 44% Information theory · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Approximation and online algorithms › online algorithms
prophet inequality |
0.8 | 1 | 2024 | Fundamental Limits of Throughput and Availability: Applications to prophet inequalities and transaction fee mechanism design · EC 2024 |
Algorithmic game theory and mechanism design › mechanism design
transaction fee mechanism design |
0.8 | 1 | 2024 | Fundamental Limits of Throughput and Availability: Applications to prophet inequalities and transaction fee mechanism design · EC 2024 |
Information theory › probability theory › measure concentration
concentration inequalities |
0.2 | 1 | 2024 | Fundamental Limits of Throughput and Availability: Applications to prophet inequalities and transaction fee mechanism design · EC 2024 |
Methods — techniques the papers use, named apart from their topics
probability bounds · 0.8concentration inequalities · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Fundamental Limits of Throughput and Availability: Applications to prophet inequalities and transaction fee mechanism designabstractThis paper studies the fundamental limits of availability and throughput for independent and heterogeneous demands of a limited resource. Availability is the probability that the demands are below the capacity of the resource. Throughput is the expected fraction of the resource that is utilized by the demands. We offer a concentration inequality generator that gives lower bounds on feasible availability and throughput pairs with a given capacity and independent but not necessarily identical distributions of up-to-unit demands. We show that availability and throughput cannot both be poor. These bounds are analogous to tail inequalities on sums of independent random variables, but hold throughout the support of the demand distribution. This analysis gives analytically tractable bounds supporting the unit-demand characterization of Chawla et al. [2023] and generalizes to up-to-unit demands. Our bounds also provide an approach towards improved multi-unit prophet inequalities [Hajiaghayi et al., 2007]. They have applications to transaction fee mechanism design (for blockchains) where high availability limits the probability of profitable user-miner coalitions [Chung and Shi, 2023]. Aadityan Ganesh, Jason D. Hartline, Atanu R. Sinha, Matthew vonAllmen |
EC | 4 |