Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Khademi, Aria"'
Safety goes first. Meeting and maintaining industry safety standards for robustness of artificial intelligence (AI) and machine learning (ML) models require continuous monitoring for faults and performance drops. Deep learning models are widely used
Externí odkaz:
http://arxiv.org/abs/2302.00775
This study explored how population mobility flows form commuting networks across US counties and influence the spread of COVID-19. We utilized 3-level mixed effects negative binomial regression models to estimate the impact of network COVID-19 exposu
Externí odkaz:
http://arxiv.org/abs/2010.01101
Autor:
Khademi, Aria, Honavar, Vasant
With the increasing adoption of predictive models trained using machine learning across a wide range of high-stakes applications, e.g., health care, security, criminal justice, finance, and education, there is a growing need for effective techniques
Externí odkaz:
http://arxiv.org/abs/2008.00357
Autor:
Khademi, Aria, Honavar, Vasant
ProPublica's analysis of recidivism predictions produced by Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) software tool for the task, has shown that the predictions were racially biased against African American defenda
Externí odkaz:
http://arxiv.org/abs/1911.10640
As virtually all aspects of our lives are increasingly impacted by algorithmic decision making systems, it is incumbent upon us as a society to ensure such systems do not become instruments of unfair discrimination on the basis of gender, race, ethni
Externí odkaz:
http://arxiv.org/abs/1903.11719
Publikováno v:
In Health and Place September 2022 77
Publikováno v:
Nature and Science of Sleep
Background The current gold standard for measuring sleep is polysomnography (PSG), but it can be obtrusive and costly. Actigraphy is a relatively low-cost and unobtrusive alternative to PSG. Of particular interest in measuring sleep from actigraphy i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::8a075a4467e69761beb52a84e5bba505
http://europepmc.org/articles/PMC6912004
http://europepmc.org/articles/PMC6912004