Demo Data from EDBT 2026 / reviewers in the wild / expert
Igal Milchtaich
dblp:26/5581
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-7228-3295ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 2Theory of computation · 1
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 · 100% |
Topics — the 11 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › mechanism design
information design |
0.4 | 1 | 2019 | Strategic Signaling for Selling Information Goods · IJCAI 2019 |
Algorithmic game theory and mechanism design
revenue maximization |
0.4 | 1 | 2019 | Strategic Signaling for Selling Information Goods · IJCAI 2019 |
Algorithmic game theory and mechanism design › imperfect information games
signaling |
0.4 | 1 | 2019 | Strategic Signaling for Selling Information Goods · IJCAI 2019 |
Algorithmic game theory and mechanism design
auction theory |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design › pricing
information selling |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design
mechanism design |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design › mechanism design › auction design
second-price auction |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design
social welfare |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design › imperfect information games
strategic communication |
0.3 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Algorithmic game theory and mechanism design
equilibrium analysis |
0.1 | 1 | 2019 | Strategic Signaling for Selling Information Goods · IJCAI 2019 |
Algorithmic game theory and mechanism design › mechanism design › information design
information disclosure |
0.1 | 1 | 2017 | Strategic Signaling and Free Information Disclosure in Auctions · AAAI 2017 |
Methods — techniques the papers use, named apart from their topics
equilibrium analysis · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Strategic Signaling for Selling Information GoodsabstractThis paper studies the benefit in using signaling by an information seller holding information that can completely disambiguate some uncertainty concerning the state of the world for the information buyer. We show that a necessary condition for having the information seller benefit from signaling in this model is having some ``seed of truth" in the signaling scheme used. We then introduce two natural signaling mechanisms that adhere to this condition, one where the seller pre-commits to the signaling scheme to be used and the other where she commits to use a signaling scheme that contains a ``seed of truth". Finally, we analyze the equilibrium resulting from each and show that, somehow counter-intuitively, despite the inherent differences between the two mechanisms, they are equivalent in the sense that for any equilibrium associated with the maximum revenue in one there is an equilibrium offering the seller the same revenue in the other. Shani Alkoby, David Sarne, Igal Milchtaich |
IJCAI | 3 |
| 2017 | Strategic Signaling and Free Information Disclosure in AuctionsabstractWith the increasing interest in the role information providers play in multi-agent systems, much effort has been dedicated to analyzing strategic information disclosure and signaling by such agents. This paper analyzes the problem in the context of auctions (specifically for second-price auctions). It provides an equilibrium analysis to the case where the information provider can use signaling according to some pre-committed scheme before introducing its regular (costly) information selling offering. The signal provided, publicly discloses (for free) some of the information held by the information provider. Providing the signaling is thus somehow counter intuitive as the information provider ultimately attempts to maximize her gain from selling the information she holds. Still, we show that such signaling capability can be highly beneficial for the information provider and even improve social welfare. Furthermore, the examples provided demonstrate various possible other beneficial behaviors available to the different players as well as to a market designer, such as paying the information provider to leave the system or commit to a specific signaling scheme. Finally, the paper provides an extension of the underlying model, related to the use of mixed signaling strategies. Shani Alkoby, David Sarne, Igal Milchtaich |
AAAI | 3 |
| 2007 | Congestion Games with Player-Specific Constants
Marios Mavronicolas, Igal Milchtaich, Burkhard Monien, Karsten Tiemann |
MFCS | 2 |