Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Jette Henderson"'
Autor:
Sinead A. Williamson, Jette Henderson
Publikováno v:
Information, Vol 12, Iss 10, p 392 (2021)
Understanding how two datasets differ can help us determine whether one dataset under-represents certain sub-populations, and provides insights into how well models will generalize across datasets. Representative points selected by a maximum mean dis
Externí odkaz:
https://doaj.org/article/22a41769f4ae460ab7b34eb1a851190f
Autor:
Sinead A. Williamson, Steve Draper, Christine Draper, Binnu Jesudasan, Luis Aguirre, Matt Sanchez, Shubham Sharma, Susan Michalski, Yessel Hinojosa, Shahzad Alam, Akarsh Prasad, Michael Criscolo, Valeri Alexiev, Prajna Kandarpa, Colton Lee, Mayank Chutani, Aditya Kumar, Alan H. Gee, Carlos Marin, Shorya Consul, Jette Henderson, Michael Perng, Michael Li, Joydeep Ghosh, Sara Rouhani
Publikováno v:
IJCAI
As more companies and governments build and use machine learning models to automate decisions, there is an ever-growing need to monitor and evaluate these models' behavior once they are deployed. Our team at CognitiveScale has developed a toolkit cal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b4cb131583002572da1050adf0ee173
https://doi.org/10.24963/ijcai.2020/759
https://doi.org/10.24963/ijcai.2020/759
Publikováno v:
AIES
Concerns within the machine learning community and external pressures from regulators over the vulnerabilities of machine learning algorithms have spurred on the fields of explainability, robustness, and fairness. Often, issues in explainability, rob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6ee57a4efbdc49a7e364adaec84fdf2
https://doi.org/10.1145/3375627.3375812
https://doi.org/10.1145/3375627.3375812
Autor:
Jette Henderson, Sinead A. Williamson
Publikováno v:
Information
Volume 12
Issue 10
Information, Vol 12, Iss 392, p 392 (2021)
Volume 12
Issue 10
Information, Vol 12, Iss 392, p 392 (2021)
Understanding how two datasets differ can help us determine whether one dataset under-represents certain sub-populations, and provides insights into how well models will generalize across datasets. Representative points selected by a maximum mean dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e534e7ad78c4d772566da31be9df4f8
Machine learning methods allow us to make recommendations to users in applications across fields including entertainment, dating, and commerce, by exploiting similarities in users' interaction patterns. However, in domains that demand protection of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68f16fa72302021d64229b0052291031
Publikováno v:
WWW
Proceedings of the ... International World-Wide Web Conference. International WWW Conference
Proceedings of the ... International World-Wide Web Conference. International WWW Conference
In the past few decades, there has been rapid growth in quantity and variety of healthcare data. These large sets of data are usually high dimensional (e.g. patients, their diagnoses, and medications to treat their diagnoses) and cannot be adequately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::535ebc4f683687c041da0dfb84e2e7fb
https://doi.org/10.1145/3308558.3313548
https://doi.org/10.1145/3308558.3313548
Autor:
Jimeng Sun, Joshua C. Denny, Bradley A. Malin, Abel N. Kho, Jette Henderson, Joyce C. Ho, Joydeep Ghosh
Publikováno v:
SDM
Tensor factorization is a methodology that is applied in a variety of fields, ranging from climate modeling to medical informatics. A tensor is an n-way array that captures the relationship between n objects. These multiway arrays can be factored to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b858fb5cc6d44f6e3fd489f7d325df16
https://doi.org/10.1137/1.9781611975673.80
https://doi.org/10.1137/1.9781611975673.80
Autor:
Jette, Henderson, Huan, He, Bradley A, Malin, Joshua C, Denny, Abel N, Kho, Joydeep, Ghosh, Joyce C, Ho
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2018
A computational phenotype is a set of clinically relevant and interesting characteristics that describe patients with a given condition. Various machine learning methods have been proposed to derive phenotypes in an automatic, high-throughput manner.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::a20f73a451ef6911727712f79d126b67
https://pubmed.ncbi.nlm.nih.gov/30815097
https://pubmed.ncbi.nlm.nih.gov/30815097
Publikováno v:
Journal of Medical Internet Research
Background: Researchers are developing methods to automatically extract clinically relevant and useful patient characteristics from raw healthcare datasets. These characteristics, often capturing essential properties of patients with common medical c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eebb4fa219c53af47cc0971c3f0d0696
http://europepmc.org/articles/PMC5960038
http://europepmc.org/articles/PMC5960038
BACKGROUND Researchers are developing methods to automatically extract clinically relevant and useful patient characteristics from raw healthcare datasets. These characteristics, often capturing essential properties of patients with common medical co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88b77f49951fe27bd70015adb62098e7
https://doi.org/10.2196/preprints.9610
https://doi.org/10.2196/preprints.9610