Abstract— Numerous machine-learning-based test methodologies have been proposed in recent years as a fast alternative to the standard functional testing of mixed-signal/RF integr...
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Data-driven grammatical function tag assignment has been studied for English using the Penn-II Treebank data. In this paper we address the question of whether such methods can be ...
This paper presents a simple randomised algorithm for recovering high-dimensional sparse functions, i.e. functions f : [0, 1]d → R which depend effectively only on k out of d va...
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...