Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Fox, Judy"'
Autor:
Islam, Md Khairul, Valentine, Tyler, Sue, Timothy Joowon, Karmacharya, Ayush, Benham, Luke Neil, Wang, Zhengguang, Kim, Kingsley, Fox, Judy
Interpreting deep learning time series models is crucial in understanding the model's behavior and learning patterns from raw data for real-time decision-making. However, the complexity inherent in transformer-based time series models poses challenge
Externí odkaz:
http://arxiv.org/abs/2401.15119
Currently, many contexts exist where distributed learning is difficult or otherwise constrained by security and communication limitations. One common domain where this is a consideration is in Healthcare where data is often governed by data-use-ordin
Externí odkaz:
http://arxiv.org/abs/2308.07805
Federated learning enables data sharing in healthcare contexts where it might otherwise be difficult due to data-use-ordinances or security and communication constraints. Distributed and shared data models allow models to become generalizable and lea
Externí odkaz:
http://arxiv.org/abs/2308.01529
The COVID-19 pandemic has created unprecedented challenges for governments and healthcare systems worldwide, highlighting the critical importance of understanding the factors that contribute to virus transmission. This study aimed to identify the mos
Externí odkaz:
http://arxiv.org/abs/2307.00751
Interpretable machine learning plays a key role in healthcare because it is challenging in understanding feature importance in deep learning model predictions. We propose a novel framework that uses deep learning to study feature sensitivity for mode
Externí odkaz:
http://arxiv.org/abs/2210.03258
This report describes 1) how we use Intel's Optane DCPMM in the memory Mode. We investigate the the scalability of applications on a single Optane machine, using Subgraph counting as memory-intensive graph problem. We test with various input graph an
Externí odkaz:
http://arxiv.org/abs/2109.11021
Autor:
Widanage, Chathura, Liu, Weijie, Li, Jiayu, Chen, Hongbo, Wang, XiaoFeng, Tang, Haixu, Fox, Judy
Trusted execution environments (TEE) such as Intel's Software Guard Extension (SGX) have been widely studied to boost security and privacy protection for the computation of sensitive data such as human genomics. However, a performance hurdle is often
Externí odkaz:
http://arxiv.org/abs/2107.12423
Autor:
Renz, Mark E., Chiu, Henry H., Jones, Susan, Fox, Judy, Kim, K. Jin, Presta, Leonard G., Fong, Sherman
Publikováno v:
The Journal of Cell Biology, 1994 Jun 01. 125(6), 1395-1406.
Externí odkaz:
https://www.jstor.org/stable/1616285
Autor:
Oliver Beckstein, Fox, Geoffrey Charles, Fox, Judy, David Crandall, Von Laszewski, Gregor, John Paden, Shantenu Jha, Fusheng Wang, Madhav Marathe, Anil Vullikanti, Cheatham, Thomas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78edaea2c82de1e76297670b7835ab87