We present a new implementation of the commonly used Box-fitting Least Squares (BLS) algorithm, for detection transiting exoplanets in photometric data. Unlike BLS, our - Sparse BLS (SBLS), does not use binning data into phase bins, nor it any kind grid. Thus, its efficiency depend on transit phase, and is therefore slightly better than that BLS. For sparse data, also significantly faster It pe...

A method for the construction of open approximate models from vector time series Preface PhD research is a largely open proces in which a stimulating environment plays a crucial role. I am indebted to several people and institutions that shaped such an environment for me during the years since April 1990. First and for all, I would like to thank my supervisor, Christiaan Heij. He set me on the ...

We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible sequential nature) of training data arising in reinforcement learning we employ a subspace based variant of LS-SVM that sequentially processes the data and is hence especially suited for online learning. This approach is adapte...