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I consider the monopolistic pricing of informational good. A buyer's willingness to pay for information is from inferring the unknown payoffs of actions in decision making. A monopolistic seller and the buyer each observes a private signal…

Theoretical Economics · Economics 2018-10-18 Weijie Zhong

A buyer and a seller bargain over the price of an object. Both players can build reputations for being obstinate by offering the same price over time. Before players bargain, the seller decides whether to adopt a new technology that can…

Theoretical Economics · Economics 2025-03-17 Harry Pei , Maren Vairo

As a firm varies the price of a product, consumers exhibit reference effects, making purchase decisions based not only on the prevailing price but also the product's price history. We consider the problem of learning such behavioral…

Computer Science and Game Theory · Computer Science 2017-08-31 Abbas Kazerouni , Benjamin Van Roy

We study the algorithmic problem faced by an information holder (seller) who wants to optimally sell such information to a budged-constrained decision maker (buyer) that has to undertake some action. Differently from previous, we consider…

Computer Science and Game Theory · Computer Science 2023-02-01 Matteo Castiglioni , Francesco Bacchiocchi , Alberto Marchesi , Giulia Romano , Nicola Gatti

We study the computational cost of differential privacy in terms of memory efficiency. While the trade-off between accuracy and differential privacy is well-understood, the inherent cost of privacy regarding memory use remains largely…

Cryptography and Security · Computer Science 2026-02-13 Alessandro Epasto , Xin Lyu , Pasin Manurangsi

The rise of artificial intelligence (A.I.) based systems is already offering substantial benefits to the society as a whole. However, these systems may also enclose potential conflicts and unintended consequences. Notably, people will tend…

Computers and Society · Computer Science 2020-12-23 Pedro Fernandes , Francisco C. Santos , Manuel Lopes

Training reliable deep learning models which avoid making overconfident but incorrect predictions is a longstanding challenge. This challenge is further exacerbated when learning has to be differentially private: protection provided to…

Machine Learning · Computer Science 2023-05-31 Stephan Rabanser , Anvith Thudi , Abhradeep Thakurta , Krishnamurthy Dvijotham , Nicolas Papernot

A game-theoretic model for analysing the effects of privacy on strategic communication between agents is devised. In the model, a sender wishes to provide an accurate measurement of the state to a receiver while also protecting its private…

Optimization and Control · Mathematics 2016-11-15 Farhad Farokhi , Henrik Sandberg , Iman Shames , Michael Cantoni

When learning is used to inform decisions about humans, such as for loans, hiring, or admissions, this can incentivize users to strategically modify their features, at a cost, to obtain positive predictions. The common assumption is that…

Machine Learning · Computer Science 2025-08-15 Yonatan Sommer , Ivri Hikri , Lotan Amit , Nir Rosenfeld

Human behavioural patterns exhibit selfish or competitive, as well as selfless or altruistic tendencies, both of which have demonstrable effects on human social and economic activity. In behavioural economics, such effects have…

Multiagent Systems · Computer Science 2021-04-28 Jan E. Snellman , Gerardo Iñiguez , János Kertész , R. A. Barrio , Kimmo K. Kaski

In distributed optimization and iterative consensus literature, a standard problem is for $N$ agents to minimize a function $f$ over a subset of Euclidean space, where the cost function is expressed as a sum $\sum f_i$. In this paper, we…

Cryptography and Security · Computer Science 2014-01-14 Zhenqi Huang , Sayan Mitra , Nitin Vaidya

This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play. The first part of the paper presents a…

Computer Science and Game Theory · Computer Science 2015-01-07 Omid Namvar Gharehshiran , William Hoiles , Vikram Krishnamurthy

Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the underlying training dataset; in reality a small or medium…

Computer Science and Game Theory · Computer Science 2018-08-27 Balazs Pejo , Qiang Tang , Gergely Biczok

Very recently, we are witnessing the emergence of a number of start-ups that enables individuals to sell their private data directly to brokers and businesses. While this new paradigm may shift the balance of power between individuals and…

Cryptography and Security · Computer Science 2017-01-04 Javier Parra-Arnau

Deploying machine learning models in production may allow adversaries to infer sensitive information about training data. There is a vast literature analyzing different types of inference risks, ranging from membership inference to…

We consider a setting where $n$ buyers, with combinatorial preferences over $m$ items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, from observing limited information about the results of these…

Computer Science and Game Theory · Computer Science 2014-08-29 Avrim Blum , Yishay Mansour , Jamie Morgenstern

Cyber and cyber-physical systems equipped with machine learning algorithms such as autonomous cars share environments with humans. In such a setting, it is important to align system (or agent) behaviors with the preferences of one or more…

Machine Learning · Computer Science 2022-03-22 Arezoo Rajabi , Bhaskar Ramasubramanian , Abdullah Al Maruf , Radha Poovendran

The main goal of this paper is to develop a theory of inference of player valuations from observed data in the generalized second price auction without relying on the Nash equilibrium assumption. Existing work in Economics on inferring…

Computer Science and Game Theory · Computer Science 2015-05-05 Denis Nekipelov , Vasilis Syrgkanis , Eva Tardos

We consider a feature-based personalized pricing problem in which the buyer is strategic: given the seller's pricing policy, the buyer can augment the features that they reveal to the seller to obtain a low price for the product. We model…

Optimization and Control · Mathematics 2024-08-19 Zhi Chen , Bradley Sturt , Weijun Xie

I study a model of advisors with hidden motives: a seller discloses information about an object's value to a potential buyer, who doesn't know the object's value or how profitable the object's sale is to the seller (the seller's motives). I…

Theoretical Economics · Economics 2023-05-08 Paula Onuchic
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