Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Andrew Zaldivar"'
Publikováno v:
FAT*
As more and more industries use machine learning, it's important to understand how these models make predictions, and where bias can be introduced in the process. In this tutorial we'll walk through two open source frameworks for analyzing your model
Publikováno v:
Communications of the ACM. 61:39-41
High-level guidelines for the treatment of crowdworkers.
Autor:
Timnit Gebru, Andrew Zaldivar, Simone Wu, Margaret Mitchell, Elena Spitzer, Inioluwa Deborah Raji, Ben Hutchinson, Parker Barnes, Lucy Vasserman
Publikováno v:
FAT
Trained machine learning models are increasingly used to perform high-impact tasks in areas such as law enforcement, medicine, education, and employment. In order to clarify the intended use cases of machine learning models and minimize their usage i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0be00e1c08e0830bfda0fa838b008f0f
Publikováno v:
IEEE Pervasive Computing. 8:42-49
The Nomatic prototype system and communications ecosystem automatically infers users' place, activity, and availability from sensors on their handheld devices or laptop computers and then reports this information to their instant-messaging contacts.I
Autor:
Andrew Zaldivar, Jeffrey L. Krichmar
Publikováno v:
Frontiers in neuroinformatics, vol 8, iss MAY
Zaldivar, A; & Krichmar, JL. (2014). Allen Brain Atlas-Driven Visualizations: A web-based gene expression energy visualization tool. Frontiers in Neuroinformatics, 8(MAY). doi: 10.3389/fninf.2014.00051. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/7c23670s
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics, Vol 8 (2014)
Zaldivar, A; & Krichmar, JL. (2014). Allen Brain Atlas-Driven Visualizations: A web-based gene expression energy visualization tool. Frontiers in Neuroinformatics, 8(MAY). doi: 10.3389/fninf.2014.00051. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/7c23670s
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics, Vol 8 (2014)
The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers th
Publikováno v:
ICDL-EPIROB
Neuromodulators such as dopamine (DA), serotonin (5-HT), and acetylcholine (ACh) are crucial to the representations of reward, cost, and attention respectively. Recent experiments suggest that the reward and cost of actions are also partially represe
Autor:
Andrew Zaldivar, Jeffrey L. Krichmar
Publikováno v:
Brain Structure & Function
Brain structure & function, vol 218, iss 6
Brain structure & function, vol 218, iss 6
Neuromodulatory systems originate in nuclei localized in the subcortical region of the brain and control fundamental behaviors by interacting with many areas of the central nervous system. An exploratory survey of the cholinergic, dopaminergic, norad
Publikováno v:
ICDL
Neuromodulators can have a strong effect on how organisms learn and compete for resources. Neuromodulators, such as dopamine (DA) and serotonin (5-HT), are known to be important in predicting rewards, costs, and punishments. To better understand the
Publikováno v:
CHI Extended Abstracts
Amazon Mechanical Turk (MTurk) is a crowdsourcing system in which tasks are distributed to a population of thousands of anonymous workers for completion. This system is increasingly popular with researchers and developers. Here we extend previous stu
Publikováno v:
From Animals to Animats 11 ISBN: 9783642151927
SAB
SAB
Neuromodulators can have a strong effect on how organisms cooperate and compete for resources. To better understand the effect of neuromodulation on cooperative behavior, a computational model of the dopaminergic and serotonergic systems was construc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cdf07c5d058c17af455882cbdc7bf95
https://doi.org/10.1007/978-3-642-15193-4_61
https://doi.org/10.1007/978-3-642-15193-4_61