Landslide detection by deep learning of non-nadiral and crowdsourced optical images
Sign Up to like & getrecommendations! Published in 2020 at "Landslides"
DOI: 10.1007/s10346-020-01513-4
Abstract: The recent development of mobile surveying platforms and crowdsourced geoinformation has produced a huge amount of non-validated data that are now available for research and application. In the field of risk analysis, with particular reference… read more here.
Keywords: learning; landslide detection; non nadiral; detection deep ... See more keywords
Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Regression Approach
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DOI: 10.1016/j.ifacol.2020.12.1265
Abstract: Abstract We propose a non-parametric regression methodology that enforces the regressor to be fully consistent with the sample set and the ground-truth regularity assumptions. As opposed to the Nonlinear Set Membership technique, this constraint guarantees… read more here.
Keywords: regression; non parametric; learning non; approach ... See more keywords
Learning Non-Parametric Models in Real Time via Online Generalized Product of Experts
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3190809
Abstract: In this work, we address the problem of online learning, where models must be continually updated from an incoming stream of data, while retaining past information. We develop an approach that is nonparametric, models uncertainty,… read more here.
Keywords: online generalized; non parametric; learning non; product experts ... See more keywords
Accelerating Distributed Learning in Non-Dedicated Environments
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Cloud Computing"
DOI: 10.1109/tcc.2021.3102593
Abstract: Machine learning (ML) models are increasingly trained with distributed workers possessing heterogeneous resources. In such scenarios, model training efficiency may be negatively affected by stragglers—workers that run much slower than others. Efficient model training requires… read more here.
Keywords: accelerating distributed; learning non; load; dedicated environments ... See more keywords
Federated Learning with Non-IID Data in Wireless Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2021.3108197
Abstract: Federated learning provides a promising paradigm to enable network edge intelligence in the future sixth generation (6G) systems. However, due to the high dynamics of wireless circumstances and user behavior, the collected training data is… read more here.
Keywords: non iid; federated learning; iid data; learning non ... See more keywords
Massive MIMO for Serving Federated Learning and Non-Federated Learning Users
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2023.3277037
Abstract: With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated that future wireless networks will jointly serve both FL and… read more here.
Keywords: mimo serving; non federated; federated learning; learning non ... See more keywords
Learning From Non-Practicing Registered Nurses.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of continuing education in nursing"
DOI: 10.3928/00220124-20221006-05
Abstract: One way to increase the number of RNs during a global nursing shortage is to recruit those currently not working in health care to rejoin the workforce. The goal of this project was to assess… read more here.
Keywords: working health; non practicing; learning non; registered nurses ... See more keywords