Zobrazeno 1 - 10
of 283
pro vyhledávání: '"McAfee, R. Preston"'
Online platforms and regulators face a continuing problem of designing effective evaluation metrics. While tools for collecting and processing data continue to progress, this has not addressed the problem of "unknown unknowns", or fundamental informa
Externí odkaz:
http://arxiv.org/abs/2402.14005
We study a new model of complementary valuations, which we call "proportional complementarities." In contrast to common models, such as hypergraphic valuations, in our model, we do not assume that the extra value derived from owning a set of items is
Externí odkaz:
http://arxiv.org/abs/1909.00788
In the classical secretary problem, one attempts to find the maximum of an unknown and unlearnable distribution through sequential search. In many real-world searches, however, distributions are not entirely unknown and can be learned through experie
Externí odkaz:
http://arxiv.org/abs/1708.08831
Autor:
Hummel, Patrick, McAfee, R. Preston
This paper presents models for predicted click-through rates in position auctions that take into account two possibilities that are not normally considered---that the identities of ads shown in other positions may affect the probability that an ad in
Externí odkaz:
http://arxiv.org/abs/1409.4687
Autor:
Hummel, Patrick, McAfee, R. Preston
Publikováno v:
International Economic Review, 2018 Nov 01. 59(4), 1733-1746.
Externí odkaz:
https://www.jstor.org/stable/45018820
Autor:
McAfee, R. Preston, Wiseman, Thomas
Publikováno v:
The Review of Economic Studies, 2008 Jan 01. 75(1), 317-332.
Externí odkaz:
https://www.jstor.org/stable/4626197
Publikováno v:
The American Economic Review, 2004 May 01. 94(2), 461-465.
Externí odkaz:
https://www.jstor.org/stable/3592928
Autor:
Hummel, Patrick, McAfee, R. Preston
Publikováno v:
Journal of Applied Econometrics, 2017 Nov 01. 32(7), 1314-1328.
Externí odkaz:
https://www.jstor.org/stable/26609821