Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jamie Morgenstern"'
Autor:
Hanna Wallach, Jennifer Wortman Vaughan, Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Kate Crawford, Hal Daumé
Publikováno v:
Communications of the ACM. 64:86-92
The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every c
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 26:1285-1291
We consider the problem of selecting fair divisions of a heterogeneous divisible good among a set of agents. Recent work (Cohler et al., AAAI 2011) focused on designing algorithms for computing maxsum—social welfare maximizing—allocations under t
Autor:
Sarah Dean, Jamie Morgenstern
Many projects (both practical and academic) have designed algorithms to match users to content they will enjoy under the assumption that user's preferences and opinions do not change with the content they see. Evidence suggests that individuals' pref
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbad4db4c748f29bb4ae20253f41baaa
http://arxiv.org/abs/2205.13026
http://arxiv.org/abs/2205.13026
Autor:
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé, Kate Crawford
Publikováno v:
Ethics of Data and Analytics ISBN: 9781003278290
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c145631803512c99d19d48de7dbaced8
https://doi.org/10.1201/9781003278290-23
https://doi.org/10.1201/9781003278290-23
Publikováno v:
FAccT
Training and evaluation of fair classifiers is a challenging problem. This is partly due to the fact that most fairness metrics of interest depend on both the sensitive attribute information and label information of the data points. In many scenarios
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ff3baa4a2b86b2baa6394029204d008
Autor:
Ben Hutchinson, Dylan Baker, Emily Denton, Jamie Morgenstern, Margaret Mitchell, Alex Hanna, Timnit Gebru, Nyalleng Moorosi
Publikováno v:
AIES
The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives. When considering the relevance of ethical concepts to subset selection problems, the concepts of diver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b103487c833d861d03dcd56540df18b9
http://arxiv.org/abs/2002.03256
http://arxiv.org/abs/2002.03256
Publikováno v:
Web and Internet Economics ISBN: 9783030649456
WINE
WINE
We build upon recent work by Kleinberg, Oren, and Raghavan [10, 11, 12] that considers present biased agents, who place more weight on costs they must incur now than costs they will incur in the future. They consider a graph theoretic model where age
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fc370e5a509bd7f0c320fe0b8f070aa
https://doi.org/10.1007/978-3-030-64946-3_19
https://doi.org/10.1007/978-3-030-64946-3_19
Publikováno v:
IJCAI
We study a network formation game where agents receive benefits by forming connections to other agents but also incur both direct and indirect costs from the formed connections. Specifically, once the agents have purchased their connections, an attac
Publikováno v:
UMAP (Adjunct Publication)
In this work, we investigate whether privacy and fairness can be simultaneously achieved by a single classifier in several different models. Some of the earliest work on fairness in algorithm design defined fairness as a guarantee of similar outputs
Autor:
Jamie Morgenstern, Ángel Alexander Cabrera, Will Epperson, Duen Horng Chau, Minsuk Kahng, Fred Hohman
Publikováno v:
VAST
The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implicit and expli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::174379898913235c5a1bcf68de0733fb
http://arxiv.org/abs/1904.05419
http://arxiv.org/abs/1904.05419