Alvin E. Roth

dblp:40/4003 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2018
0000-0002-8834-6481ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 2 first-authorTheory of computation · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

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
3 papers
Algorithmic game theory and mechanism design · 100%
Network and information security
1 paper
Privacy and data protection · 100%
Artificial intelligence
1 paper
Multi-agent systems · 100%

Topics — the 8 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
market design
0.312018
Market Design and Computerized Marketplaces · KDD 2018
Algorithmic game theory and mechanism design › market design › matching markets
kidney exchange
0.322013
Kidney exchange: where we've been and where we can go from here · EC 2013
Individual rationality and participation in large scale, multi-hospital kidney exchange · EC 2011
Algorithmic game theory and mechanism design › market design
matching markets
0.212013
Kidney exchange: where we've been and where we can go from here · EC 2013
Algorithmic game theory and mechanism design › mechanism design
individual rationality
0.112011
Individual rationality and participation in large scale, multi-hospital kidney exchange · EC 2011
Algorithmic game theory and mechanism design › matching
matching mechanism
0.112011
Individual rationality and participation in large scale, multi-hospital kidney exchange · EC 2011
Algorithmic game theory and mechanism design
mechanism design
0.112011
Individual rationality and participation in large scale, multi-hospital kidney exchange · EC 2011
Knowledge, reasoning and agents › Multi-agent systems
multi-agent learning
0.112007
Multi-agent learning and the descriptive value of simple models · Artif. Intell. 2007
Medical and health informatics › health-care delivery system › healthcare operations
organ allocation
0.012013
Kidney exchange: where we've been and where we can go from here · EC 2013

Methods — techniques the papers use, named apart from their topics

survey · 0.3market design · 0.3
YearPublicationVenuePosition
2018 Market Design and Computerized Marketplaces
abstract
Markets and marketplaces are ancient human artifacts, but in recent years they have become ever more important. In part this is because marketplaces are becoming computerized. Together with the introduction of smart phones, this also makes them ubiquitous. We can order car rides to the airport, plane rides to London, and hotel rooms for when we arrive, all on our smartphones. And as we do so we leave a data trail that is easily combined with other streams of data. This is changing not only how we interact with markets, but also how we manage and regard privacy. I'll discuss some recent developments in computerized markets and speculate about some still to come.
Alvin E. Roth
KDD1
2013 Kidney exchange: where we've been and where we can go from here
abstract
I'll give an overview of the growth of kidney exchange and of the computational, economic, and behavioral issues that arise. Kidney exchange has grown into an enterprise involving many hospitals and overlapping exchange networks, and in the process the set of strategic players has changed, and so has the patient pool. I'll discuss how the market design has evolved to keep pace with these changes, and further challenges that remain, for the medical community, for economists, and for computer scientists.
Alvin E. Roth
EC1
2011 Individual rationality and participation in large scale, multi-hospital kidney exchange
abstract
As multi-hospital kidney exchange clearinghouses have grown, the set of players has grown from patients and surgeons to include hospitals. Hospitals have the option of enrolling only their hard-to-match patient-donor pairs, while conducting easily arranged exchanges internally. This behavior has already started to be observed.
Itai Ashlagi, Alvin E. Roth
EC2
2007 Multi-agent learning and the descriptive value of simple models
Ido Erev, Alvin E. Roth
Artif. Intell.2