This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
We show that the standard memory-based collaborative filtering rating prediction algorithm using the Pearson correlation can be improved by adapting user ratings using linear reg...
In this paper we discuss a class of multiplicative algorithms for computing D-optimal designs for regression models on a finite design space. We prove a monotonicity result for a ...
Holger Dette, Andrey Pepelyshev, Anatoly A. Zhiglj...
In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensiona...