Results 1 to 10 of about 102,223 (178)
Minibatch Recursive Least Squares Q-Learning. [PDF]
Comput Intell Neurosci, 2021 The deep Q‐network (DQN) is one of the most successful reinforcement learning algorithms, but it has some drawbacks such as slow convergence and instability. In contrast, the traditional reinforcement learning algorithms with linear function approximation usually have faster convergence and better stability, although they easily suffer from the curse ...
Zhang C, Song Q, Meng Z.
europepmc +3 more sources
Zero attracting recursive least squares algorithms [PDF]
IEEE Transactions on Vehicular Technology, 2016 The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of ...
Chen, Sheng, Gao, Junbin, Hong, Xia
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Recursive least squares background prediction of univariate syndromic surveillance data [PDF]
BMC Medical Informatics and Decision Making, 2009 Background Surveillance of univariate syndromic data as a means of potential indicator of developing public health conditions has been used extensively.
Burkom Howard, Najmi Amir-Homayoon
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Stochastic Gradient versus Recursive Least Squares Learning [PDF]
SSRN Electronic Journal, 2006 In this paper we perform an in—depth investigation of relative merits of two adaptive learning algorithms with constant gain, Recursive Least Squares (RLS) and Stochastic Gradient (SG), using the Phelps model of monetary policy as a testing ground. The
Anna Bogomolova +2 more
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Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples [PDF]
Actuators, 2018 The mechanical characterization of biological samples is a fundamental issue in biology and related fields, such as tissue and cell mechanics, regenerative medicine and diagnosis of diseases.
Paolo Di Giamberardino +3 more
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Robust Data-Reuse Regularized Recursive Least-Squares Algorithms for System Identification Applications [PDF]
SensorsThe recursive least-squares (RLS) algorithm stands out as an appealing choice in adaptive filtering applications related to system identification problems.
Radu-Andrei Otopeleanu +5 more
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A Recursive Restricted Total Least-squares Algorithm
IEEE Transactions on Signal Processing, 2014 International audienceWe show that the generalized total least squares (GTLS) problem with a singular noise covariance matrix is equivalent to the restricted total least squares (RTLS) problem and propose a recursive method for its numerical solution ...
Gauterin, Frank +3 more
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IEEE Access, 2021 Two M-decomposed based identification algorithms are proposed for large-scale systems in this study. Since the least squares algorithms involve matrix inversion calculation, they can be inefficient for large-scale systems whose information matrices are ...
Yuejiang Ji, Lixin Lv
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Mixed-Precision Kernel Recursive Least Squares [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 Kernel recursive least squares (KRLS) is a widely used online machine learning algorithm for time series predictions. In this article, we present the mixed-precision KRLS, producing equivalent prediction accuracy to double-precision KRLS with a higher training throughput and a lower memory footprint.
JunKyu Lee +2 more
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Recursive Least Squares for Near-Lossless Hyperspectral Data Compression
Applied Sciences, 2022 The hyperspectral image compression scheme is a trade-off between the limited hardware resources of the on-board platform and the ever-growing resolution of the optical instruments.
Tie Zheng +3 more
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