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We study statistical parameter estimation in the setting of data markets. A buyer seeks to estimate a parameter based on samples that can be purchased from competing providers that differ in their data quality and provision costs. When…

Computer Science and Game Theory · Computer Science 2026-04-13 Yuchen Hu , Martin J. Wainwright , Stephen Bates

We study a setup in which a system operator hires a sensor to exert costly effort to collect accurate measurements of a value of interest over time. At each time, the sensor is asked to report his observation to the operator, and is…

Optimization and Control · Mathematics 2017-02-22 Donya G. Dobakhshari , Parinaz Naghizadeh , Mingyan Liu , Vijay Gupta

We study the design of autonomous agents that are capable of deceiving outside observers about their intentions while carrying out tasks in stochastic, complex environments. By modeling the agent's behavior as a Markov decision process, we…

Artificial Intelligence · Computer Science 2021-09-15 Yagiz Savas , Christos K. Verginis , Ufuk Topcu

The quality of probabilistic forecasts is crucial for decision-making under uncertainty. While proper scoring rules incentivize truthful reporting of precise forecasts, they fall short when forecasters face epistemic uncertainty about their…

Machine Learning · Computer Science 2025-07-18 Anurag Singh , Siu Lun Chau , Krikamol Muandet

We study whether a planner can robustly implement a state-contingent social choice function when (i) agents must incur a cost to learn the state and (ii) the planner faces uncertainty regarding agents' preferences over outcomes, information…

Theoretical Economics · Economics 2021-12-14 Harry Pei , Bruno Strulovici

We consider a principal agent project selection problem with asymmetric information. There are $N$ projects and the principal must select exactly one of them. Each project provides some profit to the principal and some payoff to the agent…

Theoretical Economics · Economics 2025-04-15 Sumit Goel , Wade Hann-Caruthers

A crucial part of data analysis is the validation of the resulting estimators, in particular, if several competing estimators need to be compared. Whether an estimator can be objectively validated is not a trivial property. If there exists…

Statistics Theory · Mathematics 2024-05-17 Tino Werner

The consumers' willingness to pay plays an important role in economic theory and in setting policy. For a market, this function can often be estimated from observed behavior -- preferences are revealed. However, economists would like to…

General Economics · Economics 2021-08-02 Edoh Y. Amiran , Joni S. James Charles

Prediction markets aggregate agents' beliefs regarding a future event, where each agent is paid based on the accuracy of its reported belief when compared to the realized outcome. Agents may strategically manipulate the market (e.g., delay…

Computer Science and Game Theory · Computer Science 2012-12-27 Ayman Ghoneim , Robert C. Williamson

In this paper, a new randomized response technique aimed at protecting respondents' privacy is proposed. It is designed for estimating the population total, or the population mean, of a quantitative characteristic. It provides a~high degree…

Methodology · Statistics 2021-01-25 Jaromir Antoch , Francesco Mola , Ondrej Vozar

We establish an approach for consensus control of opinion dynamics by introducing a liar to the classical system. The liar's aim is to steer the population towards consensus at their goal opinion by showing 'apparent opinions', or 'lies',…

Optimization and Control · Mathematics 2025-12-15 Sasha Glendinning , Susana N. Gomes , Marie-Therese Wolfram

It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true: creating a randomized truthful mechanism is essentially as easy as a…

Computer Science and Game Theory · Computer Science 2015-11-17 Moshe Babaioff , Robert D. Kleinberg , Aleksandrs Slivkins

Consider a market where a seller owns an item for sale and a buyer wants to purchase it. Each player has private information, known as their type. It can be costly and difficult for the players to reach an agreement through direct…

Computer Science and Game Theory · Computer Science 2024-10-29 Zhikang Fan , Weiran Shen

Estimating prevalence, the fraction of a population with a certain medical condition, is fundamental to epidemiology. Traditional methods rely on classification of test samples taken at random from a population. Such approaches to…

Methodology · Statistics 2022-03-25 Paul Patrone , Anthony Kearsley

In this paper, we study belief elicitation about an uncertain future event, where the reports will affect a principal's decision. We study two problems that can arise in this setting: (1) Agents may have an interest in the outcome of the…

Computer Science and Game Theory · Computer Science 2023-03-01 Manuel Wuthrich , Mark York , David C. Parkes

We study the problem of fairly and efficiently allocating a set of items among strategic agents with additive valuations, where items are either all indivisible or all divisible. When items are goods, numerous positive and negative results…

Computer Science and Game Theory · Computer Science 2025-07-08 Bo Li , Biaoshuai Tao , Fangxiao Wang , Xiaowei Wu , Mingwei Yang , Shengwei Zhou

We consider the problem of estimating confidence intervals for the mean of a random variable, where the goal is to produce the smallest possible interval for a given number of samples. While minimax optimal algorithms are known for this…

Machine Learning · Statistics 2020-06-19 Shengjia Zhao , Christopher Yeh , Stefano Ermon

The legitimacy of bottom-up democratic processes for the distribution of public funds by policy-makers is challenging and complex. Participatory budgeting is such a process, where voting outcomes may not always be fair or inclusive.…

Multiagent Systems · Computer Science 2023-07-25 Srijoni Majumdar , Evangelos Pournaras

The goal of a scientific investigation is to find answers to specific questions. In geosciences this is typically achieved by solving an inference or inverse problem and interpreting the solution. However, the answer obtained is often…

Geophysics · Physics 2022-01-05 Xin Zhang , Andrew Curtis

There is a growing trend among statistical agencies to explore non-probability data sources for producing more timely and detailed statistics, while reducing costs and respondent burden. Coverage and measurement error are two issues that…

Methodology · Statistics 2024-09-19 Lyndon Ang , Robert Clark , Bronwyn Loong , Anders Holmberg