Abstract In this paper we study performance tradeoffs of fairness algorithms for ring networks with spatial bandwidth reuse, by using two measures: (i) the fairness cycle size as a complexity measure, and (ii) the Max-Min optimal fairness criterion as a throughput measure. The fairness cycle size is determined by the number of communication links involved in every instance of the fairness algor...

In multi-access wireless networks, transmission scheduling is a key component that determines the efficiency and fairness of wireless spectrum allocation. At one extreme, greedy opportunistic scheduling that allocates airtime to the user with the largest instantaneous channel gain achieves the optimal spectrum efficiency and transmission reliability but the poorest user-level fairness. At the o...

We study fairness in collaborative-filtering recommender systems, which are sensitive to discrimination that exists in historical data. Biased data can lead collaborative filtering methods to make unfair predictions against minority groups of users. We identify the insufficiency of existing fairness metrics and propose four new metrics that address different forms of unfairness. These fairness ...

Manipulations of outcome favorability and outcome fairness are frequently treated as interchangeable, and assumed to have redundant effects. Perceptions of outcome fairness and outcome favorability are similarly presumed to have common antecedents and consequences. This research tested the empirical foundation of these assumptions by conducting a meta-analytic review of the justice literature (...

Liveness/Fairness plays an important role in software specification, verification and development. Existing event-based compositional models are safety-centric. In this paper, we describe a framework for systematically specifying and verifying event-based systems under fairness assumptions. We introduce different event annotations to associate fairness constraints with individual events. Fairne...

We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and span the range from group fairness to strong individual fairness. We study the accuracy-fairness trade-off on any given dataset, and we measure the severity of this trade-off via a numerical quantity we call the Price of...

In wireless networks many nodes contend for available resources creating a challenge in resource allocation. With shared resources, fairness in allocation is a serious issue. Fairness metrics have been defined to measure the fairness level of resource decisions in allocations. Therefore, fairness metrics significantly influence network and node performances emphasizing the need for due diligenc...

Competency-based medical education systems allow institutions to individualize teaching practices to meet the needs of diverse learners. Yet, the focus on continuous improvement and individualization of curricula does not exempt programs from treating learners in a fair manner. When learners fail to meet key competencies and are placed on probation or dismissed from training programs, issues of...