In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Stanford dependencies are widely used in natural language processing as a semanticallyoriented representation, commonly generated either by (i) converting the output of a constitu...
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...
In this paper, we introduce 13 program slicing metrics for C language programs. These metrics use program slice information to measure the size, complexity, coupling, and cohesion...