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In this talk, I will describe a moving sphere approach to a class of integral equations with bubble-type kernel. This class of equations comes from higher-order elliptic equations on the standard sphe...
We study the detailed structure (in a large sample) of the self-consistent estimators of the survival functions with doubly censored data. We also introduce the kernel-type density estimators based on...
We prove two-sided estimates of heat kernels on non-parabolic Riemannian manifolds with ends, assuming that the heat kernel on each end separately satisfies the Li-Yau estimate. Résumé. — Nous obte...
We study how bounds on the local geometry of a Riemannian polyhedral complex yield uniform local Poincar′e inequalities. These inequalities have a variety of applications, including bounds on the he...
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel itself from given train...
We present a new adaptive fast multipole algorithm and its parallel implementation. The algorithm is kernel-independent in the sense that the evaluation of pairwise interactions does not rely on any a...
We present a new fast multipole method for particle simulations. The main feature of our algorithm is that it does not require the implementation of multipole expansions of the underlying kernel, and ...
This paper presents a new directional multilevel algorithm for solving N-body or N-point problems with highly oscillatory kernels. We address the problem by first proving that the interaction between ...
HORSESHOES IN MULTIDIMENSIONAL SCALING AND KERNEL METHODS。
We investigate the discretization of of an electron-optical phonon scattering using a nite volume method. The discretization is conservative in mass and is essentially based on an energy point of v...
Much of the natural variation for a complex trait can be explained by variation in DNA sequence levels. As part of sequence variation, gene-gene interaction has been ubiquitously observed in nature, w...
Functional Near-Infrared spectroscopy (fNIRS) is an emerging non-invasive brain computer interface (BCI) modality that measures changes in haemoglobin concentrations in the cortical tissue. To date mo...
In this paper we extend support vector machines from reproducing kernel Hilbert spaces into reproducing kernel Banach spaces whose reproducing kernels can be defined on nonsymmetric domains. Using the...
A kernel method is proposed to estimate the condensed density of the generalized eigenvalues of pencils of Hankel matrices whose elements have a joint noncentral Gaussian distribution with nonidentica...

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