Results 31 to 40 of about 23,749 (256)
Convex Factorization Machine for Regression
CoRR, 2015 We propose the convex factorization machine (CFM), which is a convex variant of the widely used Factorization Machines (FMs). Specifically, we employ a linear+quadratic model and regularize the linear term with the $\ell_2$-regularizer and the quadratic term with the trace norm regularizer.
Yamada, Makoto +8 more
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Isotonic and Convex Regression: A Review of Theory, Algorithms, and Applications
MathematicsShape-restricted regression provides a flexible framework for estimating an unknown relationship between input variables and a response when little is known about the functional form, but qualitative structural information is available. In many practical
Eunji Lim
doaj +1 more source
Journal of Statistical Software, 2014 Convex optimization now plays an essential role in many facets of statistics. We briefly survey some recent developments and describe some implementations of these methods in R .
Roger Koenker, Ivan Mizera
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An Efficient Minimax Optimal Estimator For Multivariate Convex Regression
CoRR, 2022 This work studies the computational aspects of multivariate convex regression in dimensions $d \ge 5$. Our results include the \emph{first} estimators that are minimax optimal (up to logarithmic factors) with polynomial runtime in the sample size for both $L$-Lipschitz convex regression, and $Γ$-bounded convex regression under polytopal support.
Gil Kur, Eli Putterman
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pyStoNED: A Python Package for Convex Regression and Frontier Estimation
Journal of Statistical SoftwareShape-constrained nonparametric regression is a growing area in econometrics, statistics, operations research, machine learning, and related fields.
Sheng Dai +3 more
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On convex regression estimators
, 2010 A new nonparametric estimator of a convex regression function in any dimension is proposed and its convergence properties are studied. We start by using any estimator of the regression function and we \emph{convexify} it by taking the convex envelope of a sample of the approximation obtained.
Aguilera, Néstor E. +2 more
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A parallel method for large scale convex regression problems [PDF]
53rd IEEE Conference on Decision and Control, 2014 Convex regression (CR) problem deals with fitting a convex function to a finite number of observations. It has many applications in various disciplines, such as statistics, economics, operations research, and electrical engineering. Computing the least squares (LS) estimator via solving a quadratic program (QP) is the most common technique to fit a ...
Necdet S. Aybat, Zi Wang 0007
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Advanced Engineering Materials, EarlyView.Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Remote SensingThe non-redescending convex functions degrade the filtering robustness, whereas the redescending non-convex functions improve filtering robustness, but they tend to converge towards local minima.
Shoupeng Li, Weiwei Liu
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Advanced Functional Materials, EarlyView.Geometry‐driven design of soft cellular metamaterials is systematically investigated by combining experiments, finite element modeling, and statistical prediction. The study quantifies how unit cell geometry and material properties govern stiffness, instability, densification, and energy absorption.
Alice Berardo +4 more
wiley +1 more source