Demo Data from SIGIR 2026 / reviewers in the wild / expert
Pramod Vaidyanathan
dblp:52/8860
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory 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
1 paper |
Algorithmic game theory and mechanism design · 91% Mathematical optimization · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design
equilibrium computation |
0.1 | 1 | 2010 | Information concealing games · IEEE Trans. Inf. Theory 2010 |
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
perfect bayesian equilibrium |
0.1 | 1 | 2010 | Information concealing games · IEEE Trans. Inf. Theory 2010 |
Algorithmic game theory and mechanism design › imperfect information games
signaling game |
0.1 | 1 | 2010 | Information concealing games · IEEE Trans. Inf. Theory 2010 |
Mathematical optimization
linear programming |
0.0 | 1 | 2010 | Information concealing games · IEEE Trans. Inf. Theory 2010 |
Methods — techniques the papers use, named apart from their topics
linear programming · 0.1approximation algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Information concealing gamesabstractA system with ann-dimensional state vector and acontrollerand anactoris considered. The controller has complete information about the system state, and reveals a certain “minimum” amount of information to the actor. The actor takes certain actions based on the information the controller reveals, and the actions fetch certain utilities for each entity. Both the controller and actor seek to maximize their individual utilities by respectively selecting the information to reveal and the actions to adopt. This decision problem forms the basis of several technical and social systems, and can be formulated as a signaling game. It is shown that the Perfect Bayesian Equilibrium of this game has several counterintuitive properties and can be obtained as a saddle point of a different two person zero sum game. The computation time for saddle points using standard linear programs however turns out to be superexponential inn, which leads to computational intractability even for moderaten. Algorithms for computing saddle point policies using a computation time that is exponential innare presented. Finally, simple linear time computable policies that approximate the saddle-point policies within guaranteeable approximation ratios are obtained. Saswati Sarkar, Eitan Altman, Pramod Vaidyanathan |
IEEE Trans. Inf. Theory | 3 |