Results 11 to 20 of about 2,020,990 (315)
Learning rates for kernel-based expectile regression [PDF]
Machine Learning, 2018 Conditional expectiles are becoming an increasingly important tool in finance as well as in other areas of applications. We analyse a support vector machine type approach for estimating conditional expectiles and establish learning rates that are minimax optimal modulo a logarithmic factor if Gaussian RBF kernels are used and the desired expectile is ...
Muhammad Farooq, Ingo Steinwart
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Modeling and CFD Simulation of Regression Rate in Hybrid Rocket Motors
Fire, 2023 As the research on hybrid rocket motors advances, more accurate tools are needed to estimate the performance of the system by determining its fundamental parameters. One of them is certainly the regression rate of the solid fuel.
Alessandro Rampazzo, Francesco Barato
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Minimax Rate of Testing in Sparse Linear Regression [PDF]
Automation and Remote Control, 2019 We consider the problem of testing the hypothesis that the parameter of linear regression model is 0 against an s-sparse alternative separated from 0 in the l2-distance. We show that, in Gaussian linear regression model with p < n, where p is the dimension of the parameter and n is the sample size, the non-asymptotic minimax rate of testing has the ...
Carpentier, Alexandra +4 more
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Forecasting exchange rates: A robust regression approach [PDF]
International Journal of Forecasting, 2005 The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data ...
PREMINGER, Arie, FRANCK, Raphael
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Optimal Rates of Distributed Regression with Imperfect Kernels
J. Mach. Learn. Res., 2020 Distributed machine learning systems have been receiving increasing attentions for their efficiency to process large scale data. Many distributed frameworks have been proposed for different machine learning tasks. In this paper, we study the distributed kernel regression via the divide and conquer approach.
Hongwei Sun, Qiang Wu 0003
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Learning Rates of Least-Square Regularized Regression [PDF]
Foundations of Computational Mathematics, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qiang Wu 0003 +2 more
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Study on Thermal Degradation Characteristics and Regression Rate Measurement of Paraffin-Based Fuel
Energies, 2015 Paraffin fuel has been found to have a regression rate that is higher than conventional HTPB (hydroxyl-terminated polybutadiene) fuel and, thus, presents itself as an ideal energy source for a hybrid rocket engine.
Songqi Hu +4 more
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Energies, 2019 In this paper, the effect of sudden expansion ratio of solid fuel ramjet (SFRJ) combustor is numerically investigated with swirl flow. A computational fluid dynamics (CFD) code is written in FORTRAN to simulate the combustion and flow patterns in the ...
Weixuan Li +3 more
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A Study of Count Regression Models for Mortality Rate
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021 This paper discusses how overdispersed count data to be fit. Poisson regression model, Negative Binomial 1 regression model (NEGBIN 1) and Negative Binomial regression 2 (NEGBIN 2) model were proposed to fit mortality rate data.
Anwar Fitrianto
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Regression-adjusted abandonment rate for first patiromer prescriptions (all p<0.001).
, 2023 Regression-adjusted abandonment rate for first patiromer prescriptions (all ...
Charuhas V. Thakar (6236306) +3 more
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