We present an artificially simulated dataset (TIED) constructed so that there are many minimal sets of variables with maximal predictivity (i.e., Markov boundaries) and likewise m...
In this paper we investigate the problem of evaluating ranked lists of biomarkers, which are typically an output of the analysis of high-throughput data. This can be a list of pro...
We argue that producing maintainable high-performance implementations of finite element methods for multiple targets requires that they are written using a high-level domain-speci...
This article addresses the modeling of reverberant recording environments in the context of under-determined convolutive blind source separation. We model the contribution of each ...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...