WitrynaEach pool supports three properties: schedulingMode: This can be FIFO or FAIR, to control whether jobs within the pool queue up behind each other (the default) or share the pool’s resources fairly. weight: This controls the pool’s share of the cluster relative to other pools. By default, all pools have a weight of 1. WitrynaThis paper presents a polynomial-time algorithm for computing a locally fair partition if one exists, and considers input models where there are “runs” of red and blue points. We model the societal task of redistricting political districts as a partitioning problem: Given a set of n points in the plane, each belonging to one of two parties, and a parameter …
dblp: Shao-Heng Ko
WitrynaHowever, the Fair Partitioning problem turns out to be computationally challenging, and we formally show that it is strongly -complete. We further provide a greedy algorithm to offer practical solution to Fair Partitioning, and show its effectiveness in lowering spatial inequality in school district funding across different states in the United ... WitrynaFollow Techofriendly onFacebook: www.facebook.com/techofriendlyofficialInstagram: www.instagram.com/techo_friendlyTwitter: www.twitter.com/techo_friendlyChec... chichen itza kids facts
How does partitioning in MapReduce exactly work?
Witryna28 cze 2024 · The partition P is locally fair if there is no deviating group with respect to P. This paper focuses on a restricted case when points lie in 1D. The problem is non-trivial even in this case. We consider both adversarial and "beyond worst-case" settings for this problem. For the former, we characterize the input parameters for which a … WitrynaI am currently pursuing a PhD in Environmental Geography from the Institute for Environmental Studies (IVM) at Vrije Universiteit in Amsterdam. With broad experience as a project manager, researcher, and educator, my research has focused on managing multiple-use landscapes for people and the environment. I bring experience … WitrynaLocally Fair Partitioning. with Pankaj Agarwal, Kamesh Munagala, Erin Taylor. In Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2024). Optimizing Item and Subgroup Configurations for Social-Aware VR Shopping. with Hsu-Chao Lai, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Philip S. Yu. google maps angers france