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.

Patricio Foncea

dblp:201/5818 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1Theory 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 · 50% Approximation and online algorithms · 33% Algorithms and data structures · 17%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › mechanism design
auction design
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017
Approximation and online algorithms
online algorithms
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017
Algorithmic game theory and mechanism design › mechanism design › simple mechanisms
posted-price mechanism
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017
Approximation and online algorithms › online algorithms
prophet inequality
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017
Algorithms and data structures › data streams › streaming algorithms
random order streams
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017
Algorithmic game theory and mechanism design
revenue maximization
0.312017
Posted Price Mechanisms for a Random Stream of Customers · EC 2017

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

competitive ratio analysis · 0.3
YearPublicationVenuePosition
2017 Posted Price Mechanisms for a Random Stream of Customers
abstract
Posted price mechanisms constitute a widely used way of selling items to strategic consumers. Although suboptimal, the attractiveness of these mechanisms comes from their simplicity and easy implementation. In this paper, we investigate the performance of posted price mechanisms when customers arrive in an unknown random order. We compare the expected revenue of these mechanisms to the expected revenue of the optimal auction in two different settings. Namely, the nonadaptive setting in which all offers are sent to the customers beforehand, and the adaptive setting in which an offer is made when a consumer arrives. For the nonadaptive case, we obtain a strategy achieving an expected revenue within at least a 1-1/e fraction of that of the optimal auction. We also show that this bound is tight, even if the customers have i.i.d. valuations for the item. For the adaptive case, we exhibit a posted price mechanism that achieves a factor 0.745 of the optimal revenue, when the customers have i.i.d. valuations for the item. Furthermore, we prove that our results extend to the prophet inequality setting and in particular our result for i.i.d. random valuations resolves a problem posed by Hill and Kertz. [13]
José Correa 0001, Patricio Foncea, Ruben Hoeksma, Tim Oosterwijk, Tjark Vredeveld
EC2