Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Takehiro Kawasaki

dblp:239/8517 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › mechanism design
auction design
0.412020
Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network · AAAI 2020
Algorithmic game theory and mechanism design
mechanism design
0.412020
Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network · AAAI 2020
Algorithmic game theory and mechanism design › mechanism design › auction design
multi-unit auction
0.412020
Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network · AAAI 2020
Algorithmic game theory and mechanism design › mechanism design › incentive compatibility
strategyproofness
0.412020
Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network · AAAI 2020

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

mechanism design · 0.4
YearPublicationVenuePosition
2020 Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network
abstract
Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naïve ones. In this paper, we first propose a mechanism that satisfies all the above properties. We then make a comprehensive comparison with two naïve mechanisms, showing that the proposed mechanism dominates them in social surplus, seller's revenue, and incentive of buyers for truth-telling. We also analyze the characteristics of the social surplus and the revenue achieved by the proposed mechanism, including the constant approximability of the worst-case efficiency loss and the complexity of optimizing revenue from the seller's perspective.
Takehiro Kawasaki, Nathanaël Barrot, Seiji Takanashi, Taiki Todo, Makoto Yokoo
AAAI1