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Effective machine learning models can automatically learn useful information from a large quantity of data and provide decisions in a high accuracy. These models may, however, lead to unfair predictions in certain sense among the population…

Machine Learning · Computer Science 2020-06-19 Mingliang Chen , Min Wu

The allocation of resources among multiple agents is a fundamental problem in both economics and computer science. In these settings, fairness plays a crucial role in ensuring social acceptability and practical implementation of resource…

Computer Science and Game Theory · Computer Science 2025-06-11 Hadi Hosseini , Joshua Kavner , Samarth Khanna , Sujoy Sikdar , Lirong Xia

We present an injustice-aware innovation-diffusion model extending the Generalized Linear Threshold framework by assigning agents activation thresholds drawn from a Beta distribution to capture the stochastic nature of adoption shaped by…

Systems and Control · Electrical Eng. & Systems 2026-02-06 Lisa Piccinin , Camilla Quaresmini , Edoardo Vitale , Mara Tanelli , Valentina Breschi

In real-world classification settings, such as loan application evaluation or content moderation on online platforms, individuals respond to classifier predictions by strategically updating their features to increase their likelihood of…

Computers and Society · Computer Science 2023-09-19 Vijay Keswani , L. Elisa Celis

Reducing wealth inequality and increasing utility are critical issues. This study reveals the effects of redistribution and consumption morals on wealth inequality and utility. To this end, we present a novel approach that couples the…

General Economics · Economics 2025-04-21 Takeshi Kato , Yosuke Tanabe , Mohammad Rezoanul Hoque

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

Systematic discriminatory biases present in our society influence the way data is collected and stored, the way variables are defined, and the way scientific findings are put into practice as policy. Automated decision procedures and…

Machine Learning · Computer Science 2019-05-29 Razieh Nabi , Daniel Malinsky , Ilya Shpitser

While conventional ranking systems focus solely on maximizing the utility of the ranked items to users, fairness-aware ranking systems additionally try to balance the exposure for different protected attributes such as gender or race. To…

Machine Learning · Computer Science 2021-12-14 Omid Memarrast , Ashkan Rezaei , Rizal Fathony , Brian Ziebart

Fair division is typically framed from a centralized perspective. However, in practice resource allocation often occurs via decentralized networks. We study a decentralized variant of fair division inspired by altruistic dynamics observed…

Computer Science and Game Theory · Computer Science 2026-03-02 Joel Miller , Rishi Advani , Ian Kash , Chris Kanich , Lenore Zuck

We study economies where consumers interact independently with many monopolists. When consumer valuations over goods are correlated, correlation can distort the induced distribution of consumer surplus (information rents). We identify which…

Theoretical Economics · Economics 2026-05-29 Eric Gao , Daniel Luo

We study the question of existence and fast computation of fair and efficient allocations of indivisible resources among agents with additive valuations. As such allocations may not exist for arbitrary instances, we ask if they exist for…

Computer Science and Game Theory · Computer Science 2025-12-22 Aprup Kale , Rucha Kulkarni , Navya Garg

We develop an axiomatic framework to evaluate income distributions from the perspective of an opportunity-egalitarian social planner. Building on a formal link with the literature on decision theory under ambiguity, we characterize a class…

Theoretical Economics · Economics 2026-03-31 T. Wienand , B. Magdalou , R. Nock , P. Hufe

Recent studies on fairness in automated decision making systems have both investigated the potential future impact of these decisions on the population at large, and emphasized that imposing ''typical'' fairness constraints such as…

Machine Learning · Computer Science 2019-11-19 Joshua Williams , J. Zico Kolter

We consider a multi-organizational system in which each organization contributes processors to the global pool but also jobs to be processed on the common resources. The fairness of the scheduling algorithm is essential for the stability…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-23 Piotr Skowron , Krzysztof Rzadca

The beneficial effects of treatments vary across individuals in most studies. Treatment heterogeneity motivates practitioners to search for the optimal policy based on personal characteristics. A long-standing common practice in policy…

Statistics Theory · Mathematics 2025-01-06 Xuqiao Li , Ying Yan

Discrimination in selection problems such as hiring or college admission is often explained by implicit bias from the decision maker against disadvantaged demographic groups. In this paper, we consider a model where the decision maker…

Machine Learning · Computer Science 2021-12-13 Vitalii Emelianov , Nicolas Gast , Krishna P. Gummadi , Patrick Loiseau

Fair classification is a critical challenge that has gained increasing importance due to international regulations and its growing use in high-stakes decision-making settings. Existing methods often rely on adversarial learning or…

Machine Learning · Computer Science 2025-10-14 Alberto Sinigaglia , Davide Sartor , Marina Ceccon , Gian Antonio Susto

This paper studies an energy storage (ES) sharing model which is cooperatively invested by multiple buildings for harnessing on-site renewable utilization and grid price arbitrage. To maximize the economic benefits, we jointly consider the…

Computer Science and Game Theory · Computer Science 2021-04-06 Yu Yang , Guoqiang Hu , Costas J. Spanos

Fair top-$k$ selection, which ensures appropriate proportional representation of members from minority or historically disadvantaged groups among the top-$k$ selected candidates, has drawn significant attention. We study the problem of…

Data Structures and Algorithms · Computer Science 2026-03-31 Guangya Cai

The incorporation of fairness into the distribution network (DN) planning and operation has become a key goal of recent studies. The cost of implementing fairness, denominated the price of fairness (PoF), covers the efficiency that is…

Artificial Intelligence · Computer Science 2026-05-01 Pedro F. C. de Carvalho , Zijie Liu , Md Umar Hashmi , Dirk Van Hertem