Results 11 to 20 of about 24,904 (254)
Convex Nonparanormal Regression [PDF]
IEEE Signal Processing Letters, 2021 Quantifying uncertainty in predictions or, more generally, estimating the posterior conditional distribution, is a core challenge in machine learning and statistics. We introduce Convex Nonparanormal Regression (CNR), a conditional nonparanormal approach for coping with this task.
Yonatan Woodbridge +2 more
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Smooth Strongly Convex Regression [PDF]
2020 28th European Signal Processing Conference (EUSIPCO), 2021 6 pages, 3 ...
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EndoTac: An Endoscopic Camera-Based Tactile Sensor with High Sensitivity for Minimally Invasive Surgery. [PDF]
Adv Sci (Weinh)EndoTac presents a trocar‐compatible endoscopic vision‐based tactile sensor that uses a convex mirror to enlarge side‐facing tactile coverage during minimally invasive vessel palpation. Distorted tactile images are unwarped and processed by a learning model to estimate vascular deformation, enabling sensitive, spatially distributed tactile perception ...
Wang Y +5 more
europepmc +2 more sources
Estimating a Convex Function in Nonparametric Regression [PDF]
Scandinavian Journal of Statistics, 2006 Abstract. A new nonparametric estimate of a convex regression function is proposed and its stochastic properties are studied. The method starts with an unconstrained estimate of the derivative of the regression function, which is firstly isotonized and then integrated.
Dette, Holger, Birke, Melanie
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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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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
doaj +1 more source
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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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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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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Deep Successive Convex Approximation for Image Super-Resolution
Mathematics, 2023 Image super-resolution (SR), as one of the classic image processing issues, has attracted increasing attention from researchers. As a highly ill-conditioned, non-convex optimization issue, it is difficult for image SR to restore a high-resolution (HR ...
Xiaohui Li, Jinpeng Wang, Xinbo Liu
doaj +1 more source