Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Trent Kyono"'
Autor:
Mihaela van der Schaar, Trent Kyono
Publikováno v:
IEEE Transactions on Artificial Intelligence. 2:494-507
In many real-world settings, such as healthcare, machine learning models are trained and validated on one labeled domain and tested or deployed on another where feature distributions differ, i.e., there is covariate shift. When annotations are costly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cf20ce3949e89d4d8b05918c0a81b53
https://doi.org/10.1109/tai.2021.3101185
https://doi.org/10.1109/tai.2021.3101185
Publikováno v:
ACM Transactions on Computing for Healthcare. 2:1-24
With an aging and growing population, the number of women receiving mammograms is increasing. However, existing techniques for autonomous diagnosis do not surpass a well-trained radiologist. Therefore, to reduce the number of mammograms that require
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c86673a48840079c8f91267f6d23e5a
https://doi.org/10.1145/3453166
https://doi.org/10.1145/3453166
Autor:
Julia Yang, Jacob Lucas, Trent Kyono, Michael Abercrombie, Andrew Vanden Berg, Justin Fletcher
Publikováno v:
2022 IEEE Aerospace Conference (AERO).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28a917f621ad97a5ea2a1d417816b936
https://doi.org/10.1109/aero53065.2022.9843511
https://doi.org/10.1109/aero53065.2022.9843511
Autor:
Denis Osipychev, Panagiotis Kouvaros, Trent Kyono, Dragos D. Margineantu, Alessio Lomuscio, Yang Zheng, Francesco Leofante
Publikováno v:
International Symposium on Formal Methods
Formal Methods ISBN: 9783030908690
FM
Formal Methods ISBN: 9783030908690
FM
Neural networks are being increasingly used for efficient decision making in the aircraft domain. Given the safety-critical nature of the applications involved, stringent safety requirements must be met by these networks. In this work we present a fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db9dfbf4087d2488e0ac0f23fdb47515
http://hdl.handle.net/10044/1/94034
http://hdl.handle.net/10044/1/94034
Publikováno v:
2021 IEEE Aerospace Conference (50100).
Multi-frame blind deconvolution (MFBD) algorithms are able to produce high-resolution image reconstructions from severely degraded inputs. Often these algorithms are designed with a number of assumptions about the observing scenario and the data qual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c4697cad1081ca3f4637bcb5766c288
https://doi.org/10.1109/aero50100.2021.9438185
https://doi.org/10.1109/aero50100.2021.9438185
Selecting causal inference models for estimating individualized treatment effects (ITE) from observational data presents a unique challenge since the counterfactual outcomes are never observed. The problem is challenged further in the unsupervised do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bbd231beb676fe5ca320e78d36d374d
http://arxiv.org/abs/2102.06271
http://arxiv.org/abs/2102.06271
Publikováno v:
2020 IEEE Aerospace Conference.
Images of space objects may have their interpretability assessed with a Space-object National Imagery Interpretability Rating Scale (SNIIRS) score. The rules for such scores are specific, but the process of rating a large number of images can be time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a6b18d1c16b139119cbe09a7557d6be
https://doi.org/10.1109/aero47225.2020.9172251
https://doi.org/10.1109/aero47225.2020.9172251
Publikováno v:
2020 IEEE Aerospace Conference.
The Space-object National Imagery Interpretability Rating Scale (SNIIRS) allows human analysts to provide a quantitative score of image quality based on identification of target features. It is naturally difficult to automate this scoring process, no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edc754c41945423b587fd0fb9bbb380c
https://doi.org/10.1109/aero47225.2020.9172473
https://doi.org/10.1109/aero47225.2020.9172473
Publikováno v:
Optical Engineering. 59:1
Astronomical images collected by ground-based telescopes suffer from degradation and perturbations attributed to atmospheric turbulence. We investigate the application of convolutional neural networks (CNNs) to ground-based satellite imaging to addre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e359075df11621d7055797fdaa1b57ef
https://doi.org/10.1117/1.oe.59.5.051403
https://doi.org/10.1117/1.oe.59.5.051403
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2018 ISBN: 9783030014230
ICANN (3)
ICANN (3)
Survival analysis in the presence of multiple possible adverse events, i.e., competing risks, is a pervasive problem in many industries (healthcare, finance, etc.). Since only one event is typically observed, the incidence of an event of interest is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::891ac69f702e8f5e7f759ade81e6b92b
https://doi.org/10.1007/978-3-030-01424-7_26
https://doi.org/10.1007/978-3-030-01424-7_26