Results 311 to 320 of about 3,403,709 (354)
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Linex discrepancy for bandwidth selection
Communications in Statistics - Simulation and Computation, 2017ABSTRACTA bandwidth selection based on Linex discrepancy is proposed for kernel smoothing of periodogram. The selection minimizes Linex discrepancy between the smoothed and true spectrums. Two estimators are introduced for Linex discrepancy. The bandwidth choice outperforms some common bandwidth choices.
H. Mombeni, S. Rezaei, S. Nadarajah
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IEEE Internet of Things Journal, 2023
Along with the deployment of Industrial Internet of Things (IIoT), massive amounts of industrial data have been generated at the network edge, driving the evolution of edge machine learning (ML).
Xiuzhao Ji +4 more
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Along with the deployment of Industrial Internet of Things (IIoT), massive amounts of industrial data have been generated at the network edge, driving the evolution of edge machine learning (ML).
Xiuzhao Ji +4 more
semanticscholar +1 more source
Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices
TEST, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chacón, J. E., Duong, T.
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Scale measures for bandwidth selection
Journal of Nonparametric Statistics, 1995Both high tech and also quick and dirty methods for selecting the bandwidth of a kernel density estimator are usually based on measures of scale. An example is given to illustrate how the usual scale measures can be arbitrarily bad. This motivates development of several improved scale measures. These are assessed through simulation, and experience with
P. Janssen +3 more
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OPTIMAL BANDWIDTH SELECTION IN NONLINEAR COINTEGRATING REGRESSION
Econometric Theory, 2020We study optimal bandwidth selection in nonparametric cointegrating regression where the regressor is a stochastic trend process driven by short or long memory innovations. Unlike stationary regression, the optimal bandwidth is found to be a random sequence which depends on the sojourn time of the process. All random sequences $h_{n}$ that lie within
Wang, Qiying, Phillips, Peter C. B.
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Bandwidth selection in robust smoothing
Journal of Nonparametric Statistics, 1993In robust smoothing of regression functions of the type , the theory in automatic bandwidth selection is still lacking. This paper tries to fill the gap by looking at the use of cross-validation methods in robust smoothing. Conjectures regarding the use of a class of robust cross-validation method are made.
Leung, Denis H. Y. +2 more
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Rethinking Super-resolution: the Bandwidth Selection Problem
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019Super-resolution is the art of recovering spikes from their low-pass projections. Over the last decade specifically, several significant advancements linked with mathematical guarantees and recovery algorithms have been made.
Dmitry Batenkov, Ayush Bhandari, T. Blu
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IEEE Transactions on Services Computing
Federated Learning (FL) is a promising paradigm for massive data mining service while protecting users’ privacy. In wireless federated learning networks (WFLNs), limited communication resources and heterogeneity of user devices have essential impacts on ...
Wei Mao +3 more
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Federated Learning (FL) is a promising paradigm for massive data mining service while protecting users’ privacy. In wireless federated learning networks (WFLNs), limited communication resources and heterogeneity of user devices have essential impacts on ...
Wei Mao +3 more
semanticscholar +1 more source
Data-Driven Bandwidth Prediction Models and Automated Model Selection for Low Latency
IEEE transactions on multimedia, 2021Today's HTTP adaptive streaming solutions use a variety of algorithms to measure the available network bandwidth and predict its future values. Bandwidth prediction, which is already a difficult task, must be more accurate when lower latency is desired ...
A. Bentaleb +3 more
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