Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Abstract. We propose a privacy-preserving formulation of a linear program whose constraint matrix is partitioned into groups of columns where each group of columns and its correspo...
Functional connectivity has been widely used to reveal the dependencies between signals in complex networks such as neural networks observed from electroencephalogram (EEG) data. ...
Abstract. Traditional seizure detection algorithms act on single channels ignoring the synchronously recorded, inherently interdependent multichannel nature of EEG. However, the sp...
Borbala Hunyadi, Maarten De Vos, Marco Signoretto,...