Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Daniel Lowell"'
Publikováno v:
Frontiers in Environmental Science, Vol 9 (2021)
Recent studies have shown that predictive models can supplement or provide alternatives to E. coli-testing for assessing the potential presence of food safety hazards in water used for produce production. However, these studies used balanced training
Externí odkaz:
https://doaj.org/article/75775a780b9b4626990907545151bd9a
Autor:
Nicolas Bohm Agostini, Shi Dong, José L. Abellán, David Kaeli, Yifan Sun, Elmira Karimi, Daniel Lowell, Jing Zhou, José Cano
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 32:2448-2463
Deep Neural Networks (DNNs) have emerged as an important class of machine learning algorithms, providing accurate solutions to a broad range of applications. Sparsity in activation maps in DNN training presents an opportunity to reduce computations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::121bc8aa371bb0137165d0bdc2c0b96b
https://doi.org/10.1109/tpds.2021.3067825
https://doi.org/10.1109/tpds.2021.3067825
Akademický článek
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Autor:
Bakan, Daniel Lowell
The attached files are supplements to the author's doctoral dissertation at http://hdl.handle.net/2429/51903
Education, Faculty of
Curriculum and Pedagogy (EDCP), Department of
Graduate
Education, Faculty of
Curriculum and Pedagogy (EDCP), Department of
Graduate
Externí odkaz:
http://hdl.handle.net/2429/51863
Autor:
Delahoy, Miranda J., Shah, Hazel J., Weller, Daniel Lowell, Ray, Logan C., Smith, Kirk, McGuire, Suzanne, Trevejo, Rosalie T., Walter, Elaine Scallan, Wymore, Katie, Rissman, Tamara, McMillian, Marcy, Lathrop, Sarah, LaClair, Bethany, Boyle, Michelle M., Harris, Stic, Zablotsky-Kufel, Joanna, Houck, Kennedy, Devine, Carey J., Lau, Carey E., Tauxe, Robert V.
Publikováno v:
MMWR: Morbidity & Mortality Weekly Report; 6/30/2023, Vol. 72 Issue 26, p701-706, 6p
Akademický článek
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Autor:
Mayank Daga, Daniel Lowell, Jing Zhang, Michael Melesse, Ilya Perminov, Kamil Nasyrov, Artem Tamazov, Paul Fultz, Bragadeesh Natarajan, Vasilii Filippov, Jehandad Khan, Jing Zhou, Murali Nandhimandalam, Tejash Shah, Chao Liu
Publikováno v:
Scopus-Elsevier
Deep Learning has established itself to be a common occurrence in the business lexicon. The unprecedented success of deep learning in recent years can be attributed to: an abundance of data, availability of gargantuan compute capabilities offered by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1745cd7ee989687d8ec7984f8962c07d
http://arxiv.org/abs/1910.00078
http://arxiv.org/abs/1910.00078
Autor:
Bakan, Daniel Lowell1
Publikováno v:
Creative Approaches to Research. 2016, Vol. 9 Issue 1, p4-18. 15p.
Autor:
Steven Raasch, Daniel Lowell, Manish Gupta, Dean M. Tullsen, Vilas Sridharan, John Kalamatianos, Rajesh Gupta
Publikováno v:
DAC
Redundant Multi-Threading (RMT) provides a potentially low cost mechanism to increase GPU reliability by replicating computation at the thread level. Prior work has shown that RMT's high performance overhead stems not only from executing redundant th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::341127a38104b486467bb1fa2ac9b4c7
https://doi.org/10.1145/3061639.3062212
https://doi.org/10.1145/3061639.3062212