Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Embedded application requirements, including high performance, low power consumption and fast time to market, are uncommon in the broader domain of general purpose applications. I...
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
We improve, by using register machines, some existing universality results for specific models of P systems. P systems with membrane creation are known to generate all recursivel...
Artiom Alhazov, Rudolf Freund, Agustin Riscos-N&ua...
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...