This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
The Freebsd, gnu/Linux, Solaris, and Windows operating systems have kernels that provide comparable facilities. Interestingly, their code bases share almost no common parts, while...
Automatically detecting bugs in programs has been a long-held goal in software engineering. Many techniques exist, trading-off varying levels of automation, thoroughness of covera...