Results 1 to 10 of about 168,042 (312)
Kernel Density Estimated Linear Regression
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceRegression analysis is a cornerstone of predictive modeling, with linear regression and kernel regression standing as two of its most prominent paradigms.
Roshan Kalpavruksha +3 more
doaj +2 more sources
Kernel Smoothing in Partial Linear Models
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1988 SUMMARY Kernel smoothing is studied in partial linear models, i.e. semiparametric models of the form yi=ξi′β+f(ti)+εi(1⩽i⩽n), where the ξi are fixed known p vectors, β is an unknown vector parameter and f is a smooth but unknown function.
exaly +3 more sources
Linearized trinomials with maximum kernel [PDF]
Journal of Pure and Applied Algebra, 2022 Linearized polynomials have attracted a lot of attention because of their applications in both geometric and algebraic areas. Let $q$ be a prime power, $n$ be a positive integer and $σ$ be a generator of $\mathrm{Gal}(\mathbb{F}_{q^n}\colon\mathbb{F}_q)$. In this paper we provide closed formulas for the coefficients of a $σ$-trinomial $f$ over $\mathbb{
Santonastaso P., Zullo F.
openaire +4 more sources
Block-encoding dense and full-rank kernels using hierarchical matrices: applications in quantum numerical linear algebra [PDF]
Quantum, 2022 Many quantum algorithms for numerical linear algebra assume black-box access to a block-encoding of the matrix of interest, which is a strong assumption when the matrix is not sparse.
Quynh T. Nguyen +2 more
doaj +1 more source
Frontiers in Pharmacology, 2023 The target of the study is to predict the inhibitory effect of amide derivatives on xanthine oxidase (XO) by building several models, which are based on the theory of the quantitative structure–activity relationship (QSAR).
Xiaoda Yang +3 more
doaj +1 more source
Study on radar echo image quality control based on improved convolution technology
暴雨灾害, 2022 Based on the principle of convolution calculation,this study improves the conventional convolution method and constructs the isolated point convolution kernel,linear convolution kernel,and weak echo convolution kernel. Based on this improved conventional
Daoyang NIE, An XIAO, Houjie XIA
doaj +1 more source
Determining kernels in linear viscoelasticity
Journal of Computational Physics, 2022 In this work, we investigate the inverse problem of determining the kernel functions that best describe the mechanical behavior of a complex medium modeled by a general nonlocal viscoelastic wave equation. To this end, we minimize a tracking-type data misfit function under this PDE constraint.
Barbara Kaltenbacher +4 more
openaire +5 more sources
Linearized Kernel Dictionary Learning [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2016 In this paper we present a new approach of incorporating kernels into dictionary learning. The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an improvement in classification performance, with relation to its linear counterpart K-SVD.
Alona Golts, Michael Elad
openaire +2 more sources
The Spectral Analysis and Application of Low-degree Modified Spheroidal Hotine Kernel [PDF]
Journal of Geodesy and Geoinformation Science, 2020 The traditional spheroidal kernel results in the spectrum leakage, and the utilization rate of the removed degrees of the measured data is low. Hence, a kind of spheroidal kernel whose high- and low-degrees are both modified is introduced in this ...
MA Jian,WEI Ziqing,REN Hongfei
doaj +1 more source
Explicit Linear Kernels for Packing Problems [PDF]
Algorithmica, 2018 43 pages, 4 ...
Garnero, Valentin +3 more
openaire +3 more sources