Results 1 to 10 of about 27,189 (192)
Convex support vector regression [PDF]
European Journal of Operational ResearchNonparametric regression subject to convexity or concavity constraints is increasingly popular in economics, finance, operations research, machine learning, and statistics. However, the conventional convex regression based on the least squares loss function often suffers from overfitting and outliers.
Sheng Dai, Timo Kuosmanen
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Non-crossing convex quantile regression [PDF]
Economics Letters, 2023 Quantile crossing is a common phenomenon in shape constrained nonparametric quantile regression. A recent study by Wang et al. (2014) has proposed to address this problem by imposing non-crossing constraints to convex quantile regression. However, the non-crossing constraints may violate an intrinsic quantile property.
Sheng Dai, Timo Kuosmanen, Xun Zhou
exaly +9 more sources
Subgradient Regularized Multivariate Convex Regression at Scale
SIAM Journal on Optimization, 2023 We present new large-scale algorithms for fitting a subgradient regularized multivariate convex regression function to $n$ samples in $d$ dimensions -- a key problem in shape constrained nonparametric regression with applications in statistics, engineering and the applied sciences.
Wenyu Chen, Rahul Mazumder
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On Univariate Convex Regression [PDF]
Sankhya A, 2017 We find the local rate of convergence of the least squares estimator (LSE) of a one dimensional convex regression function when (a) a certain number of derivatives vanish at the point of interest, and (b) the true regression function is locally affine. In each case we derive the limiting distribution of the LSE and its derivative.
Bodhisattva Sen
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Convex regression in multidimensions: Suboptimality of least squares estimators
Annals of StatisticsTo appear in the Annals of ...
Fuchang Gao +2 more
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Nonconvex Sparse Logistic Regression With Weakly Convex Regularization [PDF]
IEEE Transactions on Signal Processing, 2018 In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the $\ell_0$ pseudo norm is able to better induce sparsity than the commonly used $\ell_1$ norm.
Xinyue Shen, Yuantao Gu
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Double-Convex Peroneal Tubercle Morphology and MRI-Detected Peroneal Tendon Abnormality in a Non-Lateral Referral Cohort. [PDF]
Diagnostics (Basel)Background: The peroneal tubercle demonstrates substantial morphologic variability and may influence peroneal tendon mechanics. This study evaluated whether peroneal tubercle morphology and size are associated with MRI-detected peroneal tendon ...
Gür V +7 more
europepmc +2 more sources
Convex Regression with Interpretable Sharp Partitions. [PDF]
J Mach Learn Res, 2016 We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose convex regression with interpretable sharp partitions (CRISP) for this task. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block ...
Petersen A, Simon N, Witten D.
europepmc +3 more sources
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
openaire +2 more sources
Dual active-set algorithm for optimal 3-monotone regression [PDF]
Известия Саратовского университета. Новая серия: Математика. Механика. Информатика, 2022 The paper considers a shape-constrained optimization problem of constructing monotone regression which has gained much attention over the recent years. This paper presents the results of constructing the nonlinear regression with $3$-monotone constraints.
Gudkov, Alexandr A. +2 more
doaj +1 more source