Demo Data from VLDB 2026 / reviewers in the wild / expert
Egor Ianovski
dblp:51/9924
· DBLP profile ↗
8ranked-venue papers
7as first author
2since 2021 · last 2022
0000-0001-9411-2529ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 5 first-author · 2 since 2021Theory of computation · 4 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 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
5 papers |
Algorithmic game theory and mechanism design · 82% Computational complexity · 18% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › non-cooperative game
boolean games |
0.8 | 3 | 2018 | Simulating cardinal preferences in Boolean games: A proof technique · Inf. Comput. 2018 The complexity of decision problems about equilibria in two-player Boolean games · Artif. Intell. 2018 EGuaranteeNash for Boolean Games Is NEXP-Hard · KR 2014 |
Algorithmic game theory and mechanism design › social choice
computational social choice |
0.6 | 2 | 2021 | Computing the Proportional Veto Core · AAAI 2021 The Complexity of Safe Manipulation under Scoring Rules · IJCAI 2011 |
Algorithmic game theory and mechanism design
social choice |
0.5 | 1 | 2021 | Computing the Proportional Veto Core · AAAI 2021 |
Computational complexity › game complexity
complexity of game-theoretic solution concepts |
0.3 | 1 | 2018 | The complexity of decision problems about equilibria in two-player Boolean games · Artif. Intell. 2018 |
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
nash equilibrium |
0.2 | 1 | 2014 | EGuaranteeNash for Boolean Games Is NEXP-Hard · KR 2014 |
Algorithmic game theory and mechanism design › social choice › computational social choice
voting manipulation |
0.1 | 1 | 2011 | The Complexity of Safe Manipulation under Scoring Rules · IJCAI 2011 |
Algorithmic game theory and mechanism design › social choice › computational social choice
preference representation |
0.1 | 1 | 2018 | Simulating cardinal preferences in Boolean games: A proof technique · Inf. Comput. 2018 |
Methods — techniques the papers use, named apart from their topics
polynomial-time algorithm · 0.5simulation · 0.3proof technique · 0.3scoring rules · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Welfare Effects of Strategic Voting Under Scoring Rules
Egor Ianovski, Daria Teplova, Valeriia Kuka |
EUMAS | 1 |
| 2021 | Computing the Proportional Veto CoreabstractIn social choice there often arises a conflict between the majority principle (the search for a candidate that is as good as possible for as many voters as possible), and the protection of minority rights (choosing a candidate that is not overly bad for particular individuals or groups). In a context where the latter is our main concern, veto-based rules -- giving individuals or groups the ability to strike off certain candidates from the list -- are a natural and effective way of ensuring that no minority is left with an outcome they find untenable. However, such rules often fail to be anonymous, or impose specific restrictions on the number of voters and candidates. These issues can be addressed by considering the proportional veto core -- the solution to a cooperative game where every coalition is given the power to veto a number of candidates proportional to its size. However, the naive algorithm for the veto core is exponential, and the only known rules for selecting from the veto core, with an arbitrary number of voters, violate either anonymity or neutrality. In this paper we present a polynomial time algorithm for computing the veto core and present a neutral and anonymous algorithm for selecting a candidate from it. We also show that a pessimist can manipulate the veto core in polynomial time. Egor Ianovski, Aleksei Yu. Kondratev |
AAAI | 1 |
| 2018 | The complexity of decision problems about equilibria in two-player Boolean games
Egor Ianovski, C.-H. Luke Ong |
Artif. Intell. | 1 |
| 2018 | Simulating cardinal preferences in Boolean games: A proof technique
Egor Ianovski, C.-H. Luke Ong |
Inf. Comput. | 1 |
| 2014 | EGuaranteeNash for Boolean Games Is NEXP-Hard
Egor Ianovski, C.-H. Luke Ong |
KR | 1 |
| 2014 | Complexity of Equivalence Relations and Preorders from Computability TheoryabstractAbstract We study the relative complexity of equivalence relations and preorders from computability theory and complexity theory. Given binary relationsR,S, a componentwise reducibility is defined by R≤S⇔ ∃f∀x, y[x R y↔f(x)S f(y)]. Here,fis taken from a suitable class of effective functions. For us the relations will be on natural numbers, andfmust be computable. We show that there is a ${\rm{\Pi }}_1^0$ -complete equivalence relation, but no ${\rm{\Pi }}_k^0$ -complete fork≥ 2. We show that ${\rm{\Sigma }}_k^0$ preorders arising naturally in the above-mentioned areas are ${\rm{\Sigma }}_k^0$ -complete. This includes polynomial timem-reducibility on exponential time sets, which is ${\rm{\Sigma }}_2^0$ , almost inclusion on r.e. sets, which is ${\rm{\Sigma }}_3^0$ , and Turing reducibility on r.e. sets, which is ${\rm{\Sigma }}_4^0$ . Egor Ianovski, Russell G. Miller, Keng Meng Ng, André Nies |
J. Symb. Log. | 1 |
| 2012 | Grammar Logics in Nested Sequent Calculus: Proof Theory and Decision Procedures
Alwen Tiu, Egor Ianovski, Rajeev Goré |
Advances in Modal Logic | 2 |
| 2011 | The Complexity of Safe Manipulation under Scoring RulesabstractSlinko and White, (2008) have recently introduced a new model of coalitional manipulation of voting rules under limited communication, which they call safe strategic voting. The computational aspects of this model were first studied by Hazon and Elkind, (2010), who provide polynomial-time algorithms for finding a safe strategic vote under k-approval and the Bucklin rule. In this paper, we answer an open question of Hazon and Elkind, (2010) by presenting a polynomial-time algorithm for finding a safe strategic vote under the Borda rule. Our results for Borda generalize to several interesting classes of scoring rules. Egor Ianovski, Lan Yu, Edith Elkind, Mark C. Wilson |
IJCAI | 1 |