Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Horel, Thibaut"'
We consider a Stackelberg game in which a principal (she) establishes a two-stage contract with a non-myopic agent (he) whose type is unknown. The contract takes the form of an incentive function mapping the agent's first-stage action to his second-s
Externí odkaz:
http://arxiv.org/abs/2406.12648
Modern data sets, such as those in healthcare and e-commerce, are often derived from many individuals or systems but have insufficient data from each source alone to separately estimate individual, often high-dimensional, model parameters. If there i
Externí odkaz:
http://arxiv.org/abs/2310.02864
We consider games of incomplete information in which the players' payoffs depend both on a privately observed type and an unknown but common "state of nature". External to the game, a data provider knows the state of nature and sells information to t
Externí odkaz:
http://arxiv.org/abs/2302.12223
Data buyers compete in a game of incomplete information about which a single data seller owns some payoff-relevant information. The seller faces a joint information- and mechanism-design problem: deciding which information to sell, while eliciting th
Externí odkaz:
http://arxiv.org/abs/2202.08780
Publikováno v:
In Journal of Economic Theory March 2024 216
In contrast to their seemingly simple and shared structure of independence and stationarity, L\'evy processes exhibit a wide variety of behaviors, from the self-similar Wiener process to piecewise-constant compound Poisson processes. Inspired by the
Externí odkaz:
http://arxiv.org/abs/2009.10753
Autor:
Agrawal, Rohit, Horel, Thibaut
Publikováno v:
J. Mach. Learn. Res. 22(128):1-59, 2021
The families of $f$-divergences (e.g. the Kullback-Leibler divergence) and Integral Probability Metrics (e.g. total variation distance or maximum mean discrepancies) are widely used to quantify the similarity between probability distributions. In thi
Externí odkaz:
http://arxiv.org/abs/2006.05973
The design of data markets has gained importance as firms increasingly use machine learning models fueled by externally acquired training data. A key consideration is the externalities firms face when data, though inherently freely replicable, is all
Externí odkaz:
http://arxiv.org/abs/2003.08345
This paper shows several connections between data structure problems and cryptography against preprocessing attacks. Our results span data structure upper bounds, cryptographic applications, and data structure lower bounds, as summarized next. First,
Externí odkaz:
http://arxiv.org/abs/1907.08355
We introduce hardness in relative entropy, a new notion of hardness for search problems which on the one hand is satisfied by all one-way functions and on the other hand implies both next-block pseudoentropy and inaccessible entropy, two forms of com
Externí odkaz:
http://arxiv.org/abs/1902.11202