Results 171 to 180 of about 27,189 (192)
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On uniform consistent estimators for convex regression
Journal of Nonparametric Statistics, 2011A new nonparametric estimator of a convex regression function in any dimension is proposed and its uniform convergence properties are studied.
Liliana Forzani
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Convex Regression: Theory, Practice, and Applications
, 2016 This thesis explores theoretical, computational, and practical aspects of convex (shape-constrained) regression, providing new excess risk upper bounds, a comparison of convex regression techniques with theoretical guarantee, a novel heuristic training algorithm for max-affine representations, and applications in convex stochastic programming.
Balazs, Gabor
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INFORMS Journal on Computing, 2021
We consider the problem of best [Formula: see text]-subset convex regression using [Formula: see text] observations in [Formula: see text] variables. For the case without sparsity, we develop a scalable algorithm for obtaining high quality solutions in practical times that compare favorably with other state of the art methods.
Dimitris Bertsimas, Nishanth Mundru
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We consider the problem of best [Formula: see text]-subset convex regression using [Formula: see text] observations in [Formula: see text] variables. For the case without sparsity, we develop a scalable algorithm for obtaining high quality solutions in practical times that compare favorably with other state of the art methods.
Dimitris Bertsimas, Nishanth Mundru
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Regression Models for Convex ROC Curves
Biometrics, 2000Summary. The performance of a diagnostic test is summarized by its receiver operating characteristic (ROC) curve. Under quite natural assumptions about the latent variable underlying the test, the ROC curve is convex. Empirical data on a test's performance often comes in the form of observed true positive and false positive relative frequencies under ...
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Convex Hull Ensemble Machine for Regression and Classification
Knowledge and Information Systems, 2004We propose a new ensemble algorithm called Convex Hull Ensemble Machine (CHEM). CHEM in Hilbert space is first developed and modified for regression and classification problems. We prove that the ensemble model converges to the optimal model in Hilbert space under regularity conditions.
Yongdai Kim, Jinseog Kim
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A convex version of multivariate adaptive regression splines
Computational Statistics & Data Analysis, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Diana L. Martinez +3 more
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A study on comparison of convex and non-convex penalized regression methods
2023In linear regression, penalized regression methods are used to obtain more accurate predictions depending on the structure of the data set. In addition, it is possible to determine the explanatory variables associated with the response variable by using penalized regression methods. In this study, the performances of ridge, LASSO, elastic net, adaptive
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Variable selection in convex quantile regression: L1-norm or L0-norm regularization?
European Journal of Operational Research, 2023Sheng Dai
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Fundamental barriers to high-dimensional regression with convex penalties
Annals of Statistics, 2022Andrea Montanari
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Non-convex isotonic regression via the Myersonian approach
Statistics and Probability Letters, 2021Zhenyu Cui, Chihoon Lee
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