A Suboptimal Approach to Antenna Design Problems With Kernel Regression

Household electricity demand estimation: a regression discontinuity design approach

Estimating electricity demand elasticity in different sectors has been an essential research topic. Considering the fact that pricing electricity in various countries does not follow the same rules, many econometrics methods have been developed to estimate this crucial parameter. Electricity demand elasticity is defined as the percent change in electricity consumption in response to one percent...

On a Kernel Regression Approach to Machine Translation

We present a machine translation framework based on Kernel Regression techniques. The translation process is modeled as a stringto-string mapping. For doing so, first both source and target strings are mapped to a natural vector space obtaining feature vectors. Afterwards, a translation mapping is defined from the source feature vector to the target feature vector. This translation mapping is l...

A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression

We study a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems. By developing a tool on simultaneous diagonalization of two positive definite kernels, we obtain shaper results on the minimax rates of convergence and show that smoothness regularized estimators achieve the optimal rates of convergence fo...

Kernel discriminant analysis for regression problems

In this paper, we propose a nonlinear feature extraction method for regression problems to reduce the dimensionality of the input space. Previously, a feature extraction method LDAr, a regressional version of the linear discriminant analysis, was proposed. In this paper, LDAr is generalized to a non-linear discriminant analysis by using the so called kernel trick. The basic idea is to map the i...

Kernel Group Method of Data Handling: Application to Regression Problems