Zobrazeno 1 - 10
of 602
pro vyhledávání: '"MAYO, MICHAEL"'
Autor:
Meni, Mackenzie J., Mahendrakar, Trupti, Raney, Olivia D. M., White, Ryan T., Mayo, Michael L., Pilkiewicz, Kevin
The escalating risk of collisions and the accumulation of space debris in Low Earth Orbit (LEO) has reached critical concern due to the ever increasing number of spacecraft. Addressing this crisis, especially in dealing with non-cooperative and unide
Externí odkaz:
http://arxiv.org/abs/2311.01703
Neural networks have dramatically increased our capacity to learn from large, high-dimensional datasets across innumerable disciplines. However, their decisions are not easily interpretable, their computational costs are high, and building and traini
Externí odkaz:
http://arxiv.org/abs/2308.14938
Autor:
Huang, Victoria, Sohail, Shaleeza, Mayo, Michael, Botran, Tania Lorido, Rodrigues, Mark, Anderson, Chris, Ooi, Melanie
Federated learning (FL), as an emerging artificial intelligence (AI) approach, enables decentralized model training across multiple devices without exposing their local training data. FL has been increasingly gaining popularity in both academia and i
Externí odkaz:
http://arxiv.org/abs/2305.09856
Publikováno v:
Freely available online.
Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 26, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the
Externí odkaz:
http://hdl.handle.net/10355/7025
Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an instance-scarce target domain with an explicitly different distribution. Recently published CDFSL metho
Externí odkaz:
http://arxiv.org/abs/2205.05831
Publikováno v:
In Information Sciences October 2024 681
Autor:
Daftari, Katherine1 (AUTHOR), Mayo, Michael L.2 (AUTHOR) michael.l.mayo@erdc.dren.mil, Lemasson, Bertrand H.2 (AUTHOR) bertrand.h.lemasson@usace.army.mil, Biedenbach, James M.2 (AUTHOR) james.m.biedenbach@usace.army.mil, Pilkiewicz, Kevin R.2 (AUTHOR) kevin.r.pilkiewicz@usace.army.mil
Publikováno v:
Entropy. Sep2024, Vol. 26 Issue 9, p775. 21p.
Publikováno v:
Applied Artificial Intelligence, 2020
De-identification of electronic health records (EHR) is a vital step towards advancing health informatics research and maximising the use of available data. It is a two-step process where step one is the identification of protected health information
Externí odkaz:
http://arxiv.org/abs/1901.10583