An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
The characterization of the transfer function of the power line (PL) channel is a nontrivial task that requires a truly interdisciplinary approach. Until recently, a common attribu...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The interface with the outside world has always been one of the weakest points of functional languages. It is not easy to incorporate I/O without being allowed to do side-effects....
Peter Achten, John H. G. van Groningen, Marinus J....