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We study the power of item-pricing as a tool for approximately optimizing social welfare in a combinatorial market. We consider markets with $m$ indivisible items and $n$ buyers. The goal is to set prices to the items so that, when agents…

Computer Science and Game Theory · Computer Science 2015-11-10 Michal Feldman , Nick Gravin , Brendan Lucier

Triple Modular Redundancy (TMR) is one of the most common techniques in fault-tolerant systems, in which the output is determined by a majority voter. However, the design diversity of replicated modules and/or soft errors that are more…

Hardware Architecture · Computer Science 2023-07-06 Jafar Vafaei , Omid Akbari , Muhammad Shafique , Christian Hochberger

We study correlated equilibria and coarse equilibria of simple first-price single-item auctions in the simplest auction model of full information. Nash equilibria are known to always yield full efficiency and a revenue that is at least the…

Computer Science and Game Theory · Computer Science 2017-01-09 Michal Feldman , Brendan Lucier , Noam Nisan

The property of proportional representation in approval-based committee elections has appeared in the social choice literature for over a century, and is typically understood as avoiding the underrepresentation of minorities. However, we…

Data Structures and Algorithms · Computer Science 2021-09-14 Alfonso Cevallos , Alistair Stewart

We consider a multi-agent resource allocation setting that models the assignment of papers to reviewers. A recurring issue in allocation problems is the compatibility of welfare/efficiency and fairness. Given an oracle to find a…

Computer Science and Game Theory · Computer Science 2019-08-02 Haris Aziz , Xin Huang , Nicholas Mattei , Erel Segal-Halevi

Allocating multiple scarce items across a set of individuals is an important practical problem. In the case of divisible goods and additive preferences a convex program can be used to find the solution that maximizes Nash welfare (MNW). The…

Computer Science and Game Theory · Computer Science 2019-09-25 Christian Kroer , Alexander Peysakhovich

We study a variant of classical clustering formulations in the context of algorithmic fairness, known as diversity-aware clustering. In this variant we are given a collection of facility subsets, and a solution must contain at least a…

Data Structures and Algorithms · Computer Science 2022-10-25 Suhas Thejaswi , Ameet Gadekar , Bruno Ordozgoiti , Michal Osadnik

According to the proportional allocation mechanism from the network optimization literature, users compete for a divisible resource -- such as bandwidth -- by submitting bids. The mechanism allocates to each user a fraction of the resource…

Computer Science and Game Theory · Computer Science 2014-02-17 Ioannis Caragiannis , Alexandros A. Voudouris

We consider fairness in submodular maximization subject to a knapsack constraint, a fundamental problem with various applications in economics, machine learning, and data mining. In the model, we are given a set of ground elements, each…

Data Structures and Algorithms · Computer Science 2025-05-20 Lijun Li , Chenyang Xu , Liuyi Yang , Ruilong Zhang

We study the subclass of singleton congestion games with identical and increasing cost functions, i.e., each agent tries to utilize from the least crowded resource in her accessible subset of resources. Our main contribution is a novel…

Computer Science and Game Theory · Computer Science 2020-11-04 Bugra Caskurlu , Ozgun Ekici , Fatih Erdem Kizilkaya

The use of orthogonal signaling schemes such as time-, frequency-, or code-division multiplexing (T-, F-, CDM) in multi-user systems allows for power-efficient simple receivers. It is shown in this paper that by using orthogonal signaling…

Information Theory · Computer Science 2015-05-14 Jie Gao , Sergiy A. Vorobyov , Hai Jiang

The remarkable attention which fair clustering has received in the last few years has resulted in a significant number of different notions of fairness. Despite the fact that these notions are well-justified, they are often motivated and…

Machine Learning · Computer Science 2023-06-01 John Dickerson , Seyed A. Esmaeili , Jamie Morgenstern , Claire Jie Zhang

We design an expected polynomial-time, truthful-in-expectation, (1-1/e)-approximation mechanism for welfare maximization in a fundamental class of combinatorial auctions. Our results apply to bidders with valuations that are m matroid rank…

Computer Science and Game Theory · Computer Science 2011-04-19 Shaddin Dughmi , Tim Roughgarden , Qiqi Yan

In participatory budgeting, communities collectively decide on the allocation of public tax dollars for local public projects. In this work, we consider the question of fairly aggregating the preferences of community members to determine an…

Computer Science and Game Theory · Computer Science 2016-10-17 Brandon Fain , Ashish Goel , Kamesh Munagala

We make a detailed analysis of three key algorithms (Serial Dictatorship and the naive and adaptive variants of the Boston algorithm) for the housing allocation problem, under the assumption that agent preferences are chosen iid uniformly…

Theoretical Economics · Economics 2022-06-01 Geoffrey Pritchard , Mark C. Wilson

Metric clustering is fundamental in areas ranging from Combinatorial Optimization and Data Mining, to Machine Learning and Operations Research. However, in a variety of situations we may have additional requirements or knowledge, distinct…

Machine Learning · Computer Science 2021-03-04 Brian Brubach , Darshan Chakrabarti , John P. Dickerson , Aravind Srinivasan , Leonidas Tsepenekas

We introduce two models of multiwinner elections with approval preferences and labelled candidates that take the committee's diversity into account. One model aims to find a committee with maximal diversity given a scoring function (e.g. of…

Computer Science and Game Theory · Computer Science 2026-02-13 Paula Böhm , Robert Bredereck , Till Fluschnik

We consider a cellular system with multiple Femtocells operating in a Macrocell. They are sharing a set of communication channels. Each Femtocell has multiple users requiring certain minimum rate guarantees. Each channel has a peak power…

Computer Science and Game Theory · Computer Science 2017-03-23 V. Udaya Sankar , Vinod Sharma

We revisit the recent breakthrough result of Gkatzelis et al. on (single-winner) metric voting, which showed that the optimal distortion of 3 can be achieved by a mechanism called Plurality Matching. The rule picks an arbitrary candidate…

Computer Science and Game Theory · Computer Science 2025-02-05 Fatih Erdem Kizilkaya , David Kempe

Recent studies on disparate impact in machine learning applications have sparked a debate around the concept of fairness along with attempts to formalize its different criteria. Many of these approaches focus on reducing prediction errors…

Computers and Society · Computer Science 2018-10-22 Ansh Patel