Results 41 to 50 of about 28,744 (310)
Regularized Continuous-Time Markov Model via Elastic Net
Biometrics, 2018 Summary Continuous-time Markov models are commonly used to analyze longitudinal transitions between multiple disease states in panel data, where participants’ disease states are only observed at multiple time points, and the exact state paths between observations are unknown.
Shuang Huang +7 more
openaire +3 more sources
Mathematics, 2023 Following the idea presented with regard to the elastic-net and Liu-LASSO estimators, we proposed a new penalized estimator based on the Kibria–Lukman estimator with L1-norms to perform both regularization and variable selection.
Adewale Folaranmi Lukman +5 more
doaj +1 more source
On the adaptive elastic-net with a diverging number of parameters [PDF]
, 2009 We consider the problem of model selection and estimation in situations where the number of parameters diverges with the sample size. When the dimension is high, an ideal method should have the oracle property [J. Amer. Statist. Assoc.
Zhang, Hao Helen, Zou, Hui
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Mortality Forecasting with an Age-Coherent Sparse VAR Model
Risks, 2021 This paper proposes an age-coherent sparse Vector Autoregression mortality model, which combines the appealing features of existing VAR-based mortality models, to forecast future mortality rates.
Hong Li, Yanlin Shi
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Regularized brain reading with shrinkage and smoothing [PDF]
, 2016 Functional neuroimaging measures how the brain responds to complex stimuli. However, sample sizes are modest, noise is substantial, and stimuli are high dimensional. Hence, direct estimates are inherently imprecise and call for regularization. We compare
Ramdas, Aaditya +3 more
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Joint Label-Density-Margin Space and Extreme Elastic Net for Label-Specific Features
IEEE Access, 2019 The label-specific features learning is a kind of framework for extracting the specific features of each label for classification. At present, the label-specific features algorithm is generally based on the original label space to find a particular ...
Gensheng Pei +3 more
doaj +1 more source
A Unifying View of Multiple Kernel Learning [PDF]
, 2010 Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies.
A. Rakotomamonjy +13 more
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Applied Sciences, 2021 Rock tensile strength (TS) is an important parameter for the initial design of engineering applications. The Brazilian tensile strength (BTS) test is suggested by the International Society of Rock Mechanics and the American Society for Testing Materials ...
Mohamed Yusuf Hassan, Hasan Arman
doaj +1 more source
Sparse Kernel Principal Component Analysis via Sequential Approach for Nonlinear Process Monitoring
IEEE Access, 2019 Kernel principal component analysis (KPCA) has been widely used for nonlinear process monitoring. However, since the principal components are linear combinations of all kernel functions, traditional KPCA suffers from poor interpretation and high ...
Lingling Guo +3 more
doaj +1 more source
mSystems, 2023 Toxins produced by cyanobacterial blooms in freshwater lakes are a serious public health problem. The conditions leading to toxin production are unpredictable, thereby requiring expensive sampling and monitoring programs globally.
Lindsay Collart +2 more
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