Modular Distributed Fault Diagnosis for Adaptive Structures using Local Models
Sign Up to like & getrecommendations! Published in 2020 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2020.12.862
Abstract: Abstract Adaptivity has become a promising concept in civil engineering to improve the load-bearing behavior of buildings and to reduce material consumption. However, the integrated actuators and sensors increase the complexity and adversely affect the… read more here.
Keywords: diagnosis; diagnosis adaptive; local models; distributed fault ... See more keywords
Determination of the macroscopic residual stress: Modeling and experimental evaluation of texture and local grain-interaction
Sign Up to like & getrecommendations! Published in 2020 at "Materials Characterization"
DOI: 10.1016/j.matchar.2020.110609
Abstract: Abstract When the texture is present in the sheet, it is extremely difficult to test the residual stress based on the X-ray diffraction method. Based on the two extreme traditional Voigt and Reuss models, this… read more here.
Keywords: texture; residual stress; local models; method ... See more keywords
EC-DNN: A new method for parallel training of deep neural networks
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.01.072
Abstract: Abstract Parallelization framework has become a necessity to speed up the training of deep neural networks (DNN) recently. In the typical parallelization framework, called MA-DNN, the parameters of local models are periodically averaged to get… read more here.
Keywords: training deep; deep neural; neural networks; global model ... See more keywords
Kriging Riemannian Data via Random Domain Decompositions
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2020.1853548
Abstract: Abstract Data taking value on a Riemannian manifold and observed over a complex spatial domain are becoming more frequent in applications, for example, in environmental sciences and in geoscience. The analysis of these data needs… read more here.
Keywords: kriging riemannian; riemannian data; local models; random domain ... See more keywords
Local models of astrophysical discs
Sign Up to like & getrecommendations! Published in 2017 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stx2038
Abstract: Local models of gaseous accretion discs have been successfully employed for decades to describe an assortment of small-scale phenomena, from instabilities and turbulence, to dust dynamics and planet formation. For the most part, they have… read more here.
Keywords: models astrophysical; astrophysical discs; local models;
Proofs of Network Quantum Nonlocality in Continuous Families of Distributions.
Sign Up to like & getrecommendations! Published in 2022 at "Physical review letters"
DOI: 10.1103/physrevlett.130.090201
Abstract: The study of nonlocality in scenarios that depart from the bipartite Einstein-Podolsky-Rosen setup is allowing one to uncover many fundamental features of quantum mechanics. Recently, an approach to building network-local models based on machine learning… read more here.
Keywords: network; proofs network; quantum nonlocality; local models ... See more keywords
Seasonal Local Models for Glucose Prediction in Type 1 Diabetes
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2019.2956704
Abstract: Linear empirical dynamic models have been widely used for blood glucose prediction and risks prevention in people with type 1 diabetes. More accurate blood glucose prediction models with longer prediction horizon (PH) are desirable to… read more here.
Keywords: local models; type diabetes; prediction; glucose prediction ... See more keywords
Practical Private Aggregation in Federated Learning Against Inference Attack
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3201231
Abstract: Federated learning (FL) enables multiple worker devices share local models trained on their private data to collaboratively train a machine learning model. However, local models are proved to imply the information about the private data… read more here.
Keywords: worker; federated learning; privacy; local models ... See more keywords
The test function conjecture for local models of Weil-restricted groups
Sign Up to like & getrecommendations! Published in 2020 at "Compositio Mathematica"
DOI: 10.1112/s0010437x20007162
Abstract: We prove the test function conjecture of Kottwitz and the first named author for local models of Shimura varieties with parahoric level structure attached to Weil-restricted groups, as defined by B. Levin. Our result covers… read more here.
Keywords: restricted groups; function conjecture; local models; test function ... See more keywords
More Is Not Always Better: Local Models Provide Accurate Predictions of Spectral Properties of Porphyrins
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Molecular Sciences"
DOI: 10.3390/ijms23031201
Abstract: The development of new functional materials based on porphyrins requires fast and accurate prediction of their spectral properties. The available models in the literature for absorption wavelength and extinction coefficient of the Soret band have… read more here.
Keywords: better local; extinction coefficient; always better; local models ... See more keywords