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Published in 2017 at "Annals of Operations Research"
DOI: 10.1007/s10479-016-2333-y
Abstract: This paper addresses the problem of feature selection for Multi-class Support Vector Machines. Two models involving the $$\ell _{0}$$ℓ0 (the zero norm) and the $$\ell _{2}$$ℓ2–$$\ell _{0}$$ℓ0 regularizations are considered for which two continuous approaches…
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Keywords:
class support;
feature;
feature selection;
selection multi ... See more keywords
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3
Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3247342
Abstract: In this paper, we propose new Discrete Fourier Transform (DFT)-based beamspace selection algorithms for Massive Multiple Input, Multiple Output (MIMO) receiver operating in realistic multi-user (MU) scenarios. In practical uplink scenarios, there is a power…
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Keywords:
selection multi;
multi user;
power;
selection ... See more keywords
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Published in 2021 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2020.3006279
Abstract: Learning-based techniques are increasingly effective at controlling complex systems. However, most work done so far has focused on learning control laws for individual tasks. Simultaneously learning multiple tasks on the same system is still a…
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Keywords:
task learning;
control;
selection multi;
data selection ... See more keywords
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1
Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3059872
Abstract: Feature selection aims at choosing a subset of features to represent the original feature space. In practice, however, it is hard to achieve desirable performance due to limited training data. To alleviate this issue, we…
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Keywords:
selection multi;
multi source;
feature;
feature selection ... See more keywords