We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Purpose – The aim of this paper is to analyse leadership cycles based on knowledge creation, with learning and culture as key elements for reaching leadership. Following Ikujiro...
Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable...
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...