Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to S...
Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Ha...
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Abstract— This work considers a combination classificationregression based framework with the proposal of using learned kernels in modified support vector regression to provide...