Results 21 to 30 of about 27,189 (192)
CVXR: An R Package for Disciplined Convex Optimization
Journal of Statistical Software, 2020 CVXR is an R package that provides an object-oriented modeling language for convex optimization, similar to CVX, CVXPY, YALMIP, and Convex.jl. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the ...
Anqi Fu +2 more
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Mathematics, 2020 A convex minimization problem in the form of the sum of two proper lower-semicontinuous convex functions has received much attention from the community of optimization due to its broad applications to many disciplines, such as machine learning ...
Warunun Inthakon +3 more
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Convex Mixture Regression for Quantitative Risk Assessment [PDF]
Biometrics, 2018 Summary There is wide interest in studying how the distribution of a continuous response changes with a predictor. We are motivated by environmental applications in which the predictor is the dose of an exposure and the response is a health outcome.
Canale, Antonio +2 more
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Humanities & Social Sciences Communications, 2023 This study not only aims to elucidate the curvilinear nexus between financial resilience (FR) and corporate financial performance (CFP) by drawing on the ‘too much of a good thing (TMGT)’ and ‘too little of a good thing (TLGT)’ effect but also attempts ...
XueHui Zhang, Kun-Shan Wu, Mingwen He
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Convex hull estimation of mammalian body segment parameters
Royal Society Open Science, 2021 Obtaining accurate values for body segment parameters (BSPs) is fundamental in many biomechanical studies, particularly for gait analysis. Convex hulling, where the smallest-possible convex object that surrounds a set of points is calculated, has been ...
Samuel J. Coatham +2 more
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Penalized wavelet monotone regression [PDF]
, 2007 In this paper we focus on nonparametric estimation of a constrained regression function using penalized wavelet regression techniques. This results into a convex op- timization problem under linear constraints.
Irène Gijbels +5 more
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Conditional mean embedding and optimal feature selection via positive definite kernels [PDF]
Opuscula Mathematica, 2023 Motivated by applications, we consider new operator-theoretic approaches to conditional mean embedding (CME). Our present results combine a spectral analysis-based optimization scheme with the use of kernels, stochastic processes, and constructive ...
Palle E.T. Jorgensen +2 more
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Robust Variable Selection for Single-Index Varying-Coefficient Model with Missing Data in Covariates
Mathematics, 2022 As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health.
Yunquan Song, Yaqi Liu, Hang Su
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Frontiers in Medicine, 2022 BackgroundObtaining an ideal vault is crucial in the implantable collamer lens (ICL) surgery. Prediction of the vault value is difficult since it requires the integration of multiple factors.
Zhikun Yang +7 more
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A Convex Framework for Fair Regression
CoRR, 2017 We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the rang from notions of group fairness to strong individual fairness.
Richard Berk +7 more
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