Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
We propose a multivariate methodology based on Functional Gradient Descent to estimate and forecast time-varying expected bond returns. Backtesting our procedure on US monthly dat...
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
The Boyer and Moore (BM) pattern matching algorithm is considered as one of the best, but its performance is reduced on binary data. Yet, searching in binary texts has important a...
In this paper, we present an empirical comparison of some Differential Evolution variants to solve global optimization problems. The aim is to identify which one of them is more s...