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Machine learning systems are increasingly used to make decisions about people's lives, such as whether to give someone a loan or whether to interview someone for a job. This has led to considerable interest in making such machine learning…

Machine Learning · Computer Science 2017-10-13 Daniel McNamara , Cheng Soon Ong , Robert C. Williamson

For product rating environments, similar to that of Amazon Reviews, it has been shown that the truthful elicitation of feedback is possible through mechanisms which pay buyer reports contingent on the reports of other buyers. We study…

Computer Science and Game Theory · Computer Science 2012-03-19 Jens Witkowski

Robots can learn the right reward function by querying a human expert. Existing approaches attempt to choose questions where the robot is most uncertain about the human's response; however, they do not consider how easy it will be for the…

Robotics · Computer Science 2019-10-11 Erdem Bıyık , Malayandi Palan , Nicholas C. Landolfi , Dylan P. Losey , Dorsa Sadigh

Selective classification allows models to abstain from making predictions (e.g., say "I don't know") when in doubt in order to obtain better effective accuracy. While typical selective models can be effective at producing more accurate…

Machine Learning · Computer Science 2024-06-24 Adam Fisch , Tommi Jaakkola , Regina Barzilay

In many real life situations, including job and loan applications, gatekeepers must make justified and fair real-time decisions about a person's fitness for a particular opportunity. In this paper, we aim to accomplish approximate group…

Machine Learning · Computer Science 2021-05-26 Yi Sun , Ivan Ramirez , Alfredo Cuesta-Infante , Kalyan Veeramachaneni

Peer prediction refers to a collection of mechanisms for eliciting information from human agents when direct verification of the obtained information is unavailable. They are designed to have a game-theoretic equilibrium where everyone…

Computer Science and Game Theory · Computer Science 2022-10-28 Shi Feng , Fang-Yi Yu , Yiling Chen

Automated decision support systems promise to help human experts solve multiclass classification tasks more efficiently and accurately. However, existing systems typically require experts to understand when to cede agency to the system or…

Machine Learning · Computer Science 2023-07-03 Eleni Straitouri , Lequn Wang , Nastaran Okati , Manuel Gomez Rodriguez

This paper studies repeated games where two players play multiple duopolistic games simultaneously (multimarket contact). A key assumption is that each player receives a noisy and private signal about the other's actions (private monitoring…

Computer Science and Game Theory · Computer Science 2019-11-26 Atsushi Iwasaki , Tadashi Sekiguchi , Shun Yamamoto , Makoto Yokoo

Contracts are a well-established approach for describing and analyzing behavioral aspects of web service compositions. The theory of contracts comes equipped with a notion of compatibility between clients and servers that ensures that every…

Programming Languages · Computer Science 2011-01-26 Maria Grazia Buscemi , Hernán Melgratti

Conformal prediction is a statistically rigorous method for quantifying uncertainty in models by having them output sets of predictions, with larger sets indicating more uncertainty. However, prediction sets are not inherently actionable;…

Machine Learning · Computer Science 2025-02-17 Jesse C. Cresswell , Bhargava Kumar , Yi Sui , Mouloud Belbahri

We investigate approximately optimal mechanisms in settings where bidders' utility functions are non-linear; specifically, convex, with respect to payments (such settings arise, for instance, in procurement auctions for energy). We provide…

Computer Science and Game Theory · Computer Science 2017-02-23 Amy Greenwald , Takehiro Oyakawa , Vasilis Syrgkanis

Decision-makers are often experts of their domain and take actions based on their domain knowledge. Doctors, for instance, may prescribe treatments by predicting the likely outcome of each available treatment. Actions of an expert thus…

Machine Learning · Statistics 2024-03-04 Alihan Hüyük , Qiyao Wei , Alicia Curth , Mihaela van der Schaar

We introduce a class of financial contracts involving several parties by extending the notion of a two-person game option (see Kifer (2000)) to a contract in which an arbitrary number of parties is involved and each of them is allowed to…

Mathematical Finance · Quantitative Finance 2014-05-13 Ivan Guo , Marek Rutkowski

We introduce the notions of Collective Arbitrage and of Collective Super-replication in a discrete-time setting where agents are investing in their markets and are allowed to cooperate through exchanges. We accordingly establish versions of…

Mathematical Finance · Quantitative Finance 2024-05-31 Francesca Biagini , Alessandro Doldi , Jean-Pierre Fouque , Marco Frittelli , Thilo Meyer-Brandis

We design two mechanisms that ensure that the majority preferred option wins in all equilibria. The first one is a simultaneous game where agents choose other agents to cooperate with on top of the vote for an alternative, thus overcoming…

Theoretical Economics · Economics 2023-10-12 Kirneva Margarita , Núñez Matías

Market efficiency at least requires the absence of weak arbitrage opportunities, but this is not sufficient to establish a situation where the market is sensitive, i.e., where it "fully reflects" or "rapidly adjusts to" some information…

General Finance · Quantitative Finance 2026-02-25 Gabriel Frahm

Linear contracts are ubiquitous in practice, yet optimal contract theory often prescribes complex, nonlinear structures. We provide a distributional robustness justification for linear contracts. We study a principal-agent problem where the…

Computer Science and Game Theory · Computer Science 2026-04-28 Shiliang Zuo

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2015-03-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

We explore the deliberate infusion of ambiguity into the design of contracts. We show that when the agent is ambiguity-averse and hence chooses an action that maximizes their minimum utility, the principal can strictly gain from using an…

Computer Science and Game Theory · Computer Science 2024-09-17 Paul Dütting , Michal Feldman , Daniel Peretz , Larry Samuelson

In some research evaluation systems, credit awarded to an article depends on the number of co-authors on the article with total credit to the article increasing with the number of co-authors. There are many examples of such evaluation…

Digital Libraries · Computer Science 2020-01-28 Lawrence Smolinsky