Distributed programming and object-oriented programming are two popular programming paradigms. The former is driven by advances in networking technology whereas the latter provide...
Alan C. Y. Wong, Samuel T. Chanson, Shing-Chi Cheu...
To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database al...
Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Per...
The paradigm of the proxel ("probability element") was recently introduced in order to provide a new algorithmic approach to analysing discrete-state stochastic models s...
Abstract. We introduce a concept of self-organizing Hybrid Neurofuzzy Networks (HNFN), a hybrid modeling architecture combining neurofuzzy (NF) and polynomial neural networks(PNN)....
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...