Demo Data from SIGIR 2026 / reviewers in the wild / expert
Giannis Tyrovolas
dblp:365/4900
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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
2 papers |
Algorithmic game theory and mechanism design · 94% Computational complexity · 6% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design
fair division |
0.9 | 1 | 2025 | Fraud-Proof Revenue Division on Subscription Platforms · ICML 2025 |
Algorithmic game theory and mechanism design › social choice › strategic manipulation
manipulation resistance |
0.9 | 1 | 2025 | Fraud-Proof Revenue Division on Subscription Platforms · ICML 2025 |
Algorithmic game theory and mechanism design › social choice
computational social choice |
0.8 | 1 | 2024 | Unravelling Expressive Delegations: Complexity and Normative Analysis · AAAI 2024 |
Algorithmic game theory and mechanism design › social choice › computational social choice
liquid democracy |
0.8 | 1 | 2024 | Unravelling Expressive Delegations: Complexity and Normative Analysis · AAAI 2024 |
Methods — techniques the papers use, named apart from their topics
approximation algorithm · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Fraud-Proof Revenue Division on Subscription PlatformsabstractWe study a model of subscription-based platforms where users pay a fixed fee for unlimited access to content, and creators receive a share of the revenue. Existing approaches to detecting fraud predominantly rely on machine learning methods, engaging in an ongoing arms race with bad actors. We explore revenue division mechanisms that inherently disincentivize manipulation. We formalize three types of manipulation-resistance axioms and examine which existing rules satisfy these. We show that a mechanism widely used by streaming platforms, not only fails to prevent fraud, but also makes detecting manipulation computationally intractable. We also introduce a novel rule, ScaledUserProp, that satisfies all three manipulation-resistance axioms. Finally, experiments with both real-world and synthetic streaming data support ScaledUserProp as a fairer alternative compared to existing rules. Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh, Giannis Tyrovolas |
ICML | 4 |
| 2024 | Unravelling Expressive Delegations: Complexity and Normative AnalysisabstractWe consider binary group decision-making under a rich model of liquid democracy: agents submit ranked delegation options, where each option may be a function of multiple agents' votes; e.g., "I vote yes if a majority of my friends vote yes." Such ballots are unravelled into a profile of direct votes by selecting one entry from each ballot so as not to introduce cyclic dependencies. We study delegation via monotonic Boolean functions, and two unravelling procedures: MinSum, which minimises the sum of the ranks of the chosen entries, and its egalitarian counterpart, MinMax. We provide complete computational dichotomies: MinSum is hard to compute (and approximate) as soon as any non-trivial functions are permitted, and polynomial otherwise; for MinMax the easiness results extend to arbitrary-arity logical ORs and ANDs taken in isolation, but not beyond. For the classic model of delegating to individual agents, we give asymptotically near-tight algorithms for carrying out the two procedures and efficient algorithms for finding optimal unravellings with the highest vote count for a given alternative. These algorithms inspire novel tie-breaking rules for the setup of voting to change a status quo. We then introduce a new axiom, which can be viewed as a variant of the participation axiom, and use algorithmic techniques developed earlier in the paper to show that it is satisfied by MinSum and a lexicographic refinement of MinMax (but not MinMax itself). Giannis Tyrovolas, Andrei Constantinescu 0001, Edith Elkind |
AAAI | 1 |