Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints
DOI10.1137/21M1407513zbMath1491.60051arXiv2009.04188OpenAlexW4281796895WikidataQ114074071 ScholiaQ114074071MaRDI QIDQ5089721
François Bachoc, Andrés F. López-Lopera, Olivier Roustant
Publication date: 15 July 2022
Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2009.04188
Gaussian processesreproducing kernel Hilbert spacesinequality constraintssequential designsknot allocationpiecewise multiaffine functions
Numerical smoothing, curve fitting (65D10) Gaussian processes (60G15) Applications of statistics in engineering and industry; control charts (62P30) Sequential statistical methods (62L99)
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- A numerically stable dual method for solving strictly convex quadratic programs
- Generalization of the Kimeldorf-Wahba correspondence for constrained interpolation
- Kriging of financial term-structures
- The optimal free knot spline approximation of stochastic differential equations with additive noise
- Efficient global optimization of expensive black-box functions
- Interpolation of spatial data. Some theory for kriging
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Sharp asymptotics for isotonic regression
- Limit theory in monotone function estimation
- Sharp oracle inequalities for least squares estimators in shape restricted regression
- Estimation of a convex function: Characterizations and asymptotic theory.
- Gaussian process modeling with inequality constraints
- Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors
- Maximum likelihood estimation for Gaussian processes under inequality constraints
- A supermartingale approach to Gaussian process based sequential design of experiments
- Gaussian process emulators for computer experiments with inequality constraints
- A new method for interpolating in a convex subset of a Hilbert space
- Free-knot spline approximation of stochastic processes
- Bayesian Calibration of Computer Models
- Bayesian monotone regression using Gaussian process projection
- Nonparametric Estimation under Shape Constraints
- Monotone Emulation of Computer Experiments
- Geostatistics
- 10.1162/15324430260185646
- Approximation to Data by Splines with Free Knots
- Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints
- Universal Prediction Distribution for Surrogate Models
- Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC
- Intrinsic Gaussian Processes on Complex Constrained Domains
- An algorithm for data reduction using splines with free knots
- A practical guide to splines.
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