What is she best known for?
The fields of study she is best known for:
- Algorithm
- Computer network
- Artificial intelligence
Her primary scientific interests are in Approximation algorithm, Mathematical optimization, Algorithm, Network planning and design and Theoretical computer science.
She interconnects Discrete mathematics, Social network analysis, Optimization problem and Centrality in the investigation of issues within Approximation algorithm.
Éva Tardos studies Linear programming which is a part of Mathematical optimization.
Her Algorithm research includes elements of Facility location problem, Lagrangian relaxation, Polynomial and Total cost.
Her Network planning and design study combines topics from a wide range of disciplines, such as Shapley value, Game theory, Technical report and Nash equilibrium.
Her Theoretical computer science research integrates issues from Algorithmic game theory, Algorithm engineering, Algorithmics, Game complexity and Computational geometry.
Her most cited work include:
- Maximizing the spread of influence through a social network (4896 citations)
- How bad is selfish routing (1351 citations)
- Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria (1177 citations)
What are the main themes of her work throughout her whole career to date?
Éva Tardos focuses on Approximation algorithm, Mathematical optimization, Combinatorics, Mathematical economics and Price of anarchy.
In her research on the topic of Approximation algorithm, Submodular set function is strongly related with Optimization problem.
Her study looks at the relationship between Mathematical optimization and topics such as Algorithm, which overlap with Simple, Maximum flow problem and Polynomial.
Her Combinatorics study combines topics in areas such as Discrete mathematics, Linear programming and Combinatorial optimization.
Her research investigates the connection between Mathematical economics and topics such as Common value auction that intersect with issues in Greedy algorithm.
While the research belongs to areas of Algorithmic game theory, Éva Tardos spends her time largely on the problem of Algorithmics, intersecting her research to questions surrounding Theoretical computer science and Game complexity.
She most often published in these fields:
- Approximation algorithm (27.75%)
- Mathematical optimization (26.79%)
- Combinatorics (21.05%)
What were the highlights of her more recent work (between 2012-2021)?
- Mathematical economics (20.57%)
- Price of anarchy (15.31%)
- Mathematical optimization (26.79%)
In recent papers she was focusing on the following fields of study:
Her main research concerns Mathematical economics, Price of anarchy, Mathematical optimization, Regret and Common value auction.
Her studies deal with areas such as Generalized second-price auction and Market clearing as well as Mathematical economics.
Éva Tardos interconnects Algorithm and Algorithmic game theory in the investigation of issues within Price of anarchy.
Éva Tardos works in the field of Mathematical optimization, namely Submodular set function.
Her Submodular set function research incorporates themes from Social network analysis, Viral marketing, Social network, Centrality and Heuristics.
As part of one scientific family, Éva Tardos deals mainly with the area of Common value auction, narrowing it down to issues related to the Greedy algorithm, and often Approximation algorithm, Inefficiency and Cardinality.
Between 2012 and 2021, her most popular works were:
- Maximizing the Spread of Influence through a Social Network (324 citations)
- Composable and efficient mechanisms (141 citations)
- Bounding the inefficiency of outcomes in generalized second price auctions (45 citations)
In her most recent research, the most cited papers focused on:
- Algorithm
- Computer network
- The Internet
Éva Tardos mainly focuses on Mathematical economics, Nash equilibrium, Price of anarchy, Generalized second-price auction and Repeated game.
Her Mathematical economics research includes themes of Class, Vickrey auction and Common value auction.
Her Nash equilibrium study deals with Bounding overwatch intersecting with Potential game, Congestion game and Network planning and design.
Within one scientific family, she focuses on topics pertaining to Regret under Repeated game, and may sometimes address concerns connected to Discrete mathematics.
In her articles, she combines various disciplines, including High probability and Mathematical optimization.
Her Mathematical optimization course of study focuses on Payment and Mechanism design.
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