In this paper, we present a patch-based regression framework for addressing the human. Finally, kernel regression is employed for ultimate human age or head pose. For better viewing, please see the pdf file. In this paper, we present a patch-based regression framework for addressing the human age and head pose estimation problems. Firstly, each image is.via Kernel Partial Least Squares Regressi...

The adiabatic-connection fluctuation-dissipation theorem (ACFDT) provides a formal frame work to treat the exchange-correlation energy. Under the random phase approximation (RPA), the effect of the exchange-correlation kernel is neglected, leading to the so-called EXX/RPA method. It has been shown that EXX/RPA yields overall a good description of structural properties of materials with differen...

The longitudinal, transverse and torsional wave dispersion curves in single walled carbon nanotubes (SWCNT) are used to estimate the non-local kernel for use in continuum elasticity models of nanotubes. The dispersion data for an armchair (10,10) SWCNT was obtained using lattice dynamics of SWNTs while accounting for the helical symmetry of the tubes. In our approach, the Fourier transformed ke...

An integrated 128x128 CMOS image sensor with programmable diffusion kernel for local brightness adaptation and contrast enhancement achieves local brightness adaptation by dividing each individual pixel photocurrent by the average photocurrent of the corresponding kernel. The chip is realized in 1μm standard CMOS. Pixel pitch is 47μm and total chip area is 86.4 mm2. Power dissipation is 20mW at...

The Nadaraya–Watson estimator, also known as kernel regression, is a density-based regression technique. It weights output values with the relative densities in input space. The density is measured with kernel functions that depend on bandwidth parameters. In this work we present an evolutionary bandwidth optimizer for kernel regression. The approach is based on a robust loss function, leave-on...

In this paper we propose a new 3D kernel for the recovery of 3Dorientation signatures. The kernel is a Gaussian function defined in local spherical coordinates and its Cartesian support has the shape of a truncated cone with axis in radial direction and very small angular support. A set of such kernels is obtained by uniformly sampling the 2D space of polar and azimuth angles. The projection of...

We present in this paper a new kernel-independent fast multipole method (FMM), named as FKI-FMM, for pairwise particle interactions with translation-invariant kernel functions. FKI-FMM creates, using numerical techniques, sufficiently accurate and compressive representations of a given kernel function over multi-scale interaction regions in the form of a truncated Fourier series. It provides al...

In order to better identify the fault of rotor system,one new method based on local fuzzy clustering margin fisher discriminant (LFCMFD) was proposed. For each point on manifold, the farthest point in local neighborhood and the nearest point outside local neighborhood usually constituted the local margin. LFCMFD introduced fuzzy cluster analysis algorithm, eliminated the influence of pseudo-mar...

This paper discusses a new convolution tree kernel by introducing local alignments. The main idea of the new kernel is to allow some syntactic alternations during each match between subtrees. In this paper, we give an algorithm to calculate the composite kernel. The experiment results show promising improvements on two tasks: semantic role labeling and question classification.

To asses the sensitivity of conclusions to model choices in the context of selection models for non-random dropout, several methods have been developed. None of them are without limitations. A new method called kernel weighted influence is proposed. While global and local influence approaches look upon the influence of cases, this new method looks at the influence of types of observations. The ...