Results 81 to 90 of about 871 (187)
Radial kernels and their reproducing kernel Hilbert spaces
Journal of Complexity, 2010 Let \(R\) be a continuous convex function on a Hilbert space \(H\). In learning theory, \[ A(\lambda):= \inf_{h\in H} \{\lambda\| h\|^2+ R(h)\}- \inf_{h\in H} R(h) \] is called an approximation error function. Here, \(H\) is a reproducing kernel Hilbert space (RKHS) of functions on \(\mathbb{R}^d\), i.e., such that the evaluations \(\delta_x: h\mapsto ...
Scovel, Clint +3 more
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A Characterization for reproducing kernel Hilbert spaces
Journal of Mathematical Analysis and Applications, 1974 AbstractLet G(t, s) be the Green's functions associated with N, a differential operator restricted to certain boundary conditions. Define (u, v)N = (Nu, v)L2. It is shown that the reproducing kernel Hilbert space generated by G is the same as the Hilbert-space completion with respect to ∥ · ∥N of the set of real valued functions which are in C2n and ...
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Flexible Expectile Regression in Reproducing Kernel Hilbert Spaces
Technometrics, 2017 Expectile, first introduced by Newey and Powell in 1987 in the econometrics literature, has recently become increasingly popular in risk management and capital allocation for financial institutions due to its desirable properties such as coherence and elicitability.
Yang, Yi, Zhang, Teng, Zou, Hui
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Machine Learning Based System Identification with Binary Output Data Using Kernel Methods
Journal of Telecommunications and Information TechnologyWithin the realm of machine learning, kernel methods stand out as a prominent class of algorithms with widespread applications, including but not limited to classification, regression, and identification tasks.
Rachid Fateh +7 more
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On some spaces of holomorphic functions of exponential growth on a half-plane
Concrete Operators, 2016 In this paper we study spaces of holomorphic functions on the right half-plane R, that we denote by Mpω, whose growth conditions are given in terms of a translation invariant measure ω on the closed half-plane R.
Peloso Marco M., Salvatori Maura
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A Kernel-Based Metric for Balance Assessment
Journal of Causal Inference, 2018 An important goal in causal inference is to achieve balance in the covariates among the treatment groups. In this article, we introduce the concept of distributional balance preserving which requires the distribution of the covariates to be the same in ...
Zhu Yeying +2 more
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Applied SciencesSoftware-defined networking (SDN) requires adaptive control strategies to handle dynamic traffic conditions and heterogeneous network environments.
Yedil Nurakhov +3 more
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Some Lemmas on Reproducing Kernel Hilbert Spaces [PDF]
, 2002 Reproducing kernel Hilbert spaces (RKHS) provides a framework for approximation from finite data using the idea of bounded linear functionals. The approximation problem in this case can be viewed as the inverse problem of finding the optimum operator from the Euclidean space of observations to some subspace of the RKHS.
Dodd, T.J., Harrison, R.F.
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The Convergence Rate for a
Journal of Inequalities and Applications, 2010 It is known that in the field of learning theory based on reproducing kernel Hilbert spaces the upper bounds estimate for a -functional is needed.
Xiang Dao-Hong, Sheng Bao-Huai
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Conditional Exponential Convex Functions on White Noise Spaces
AxiomsThis paper seeks to present the fundamental features of the category of conditional exponential convex functions (CECFs). Additionally, the study of continuous CECFs contributes to the characterization of convolution semigroups.
Ahmed. M. Zabel +3 more
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