Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
— Recent work has revealed a close connection between certain information theoretic divergence measures and properties of Mercer kernel feature spaces. Specifically, it has been...
This paper advocates a novel approach to the construction of secure software: controlling information flow and maintaining integrity via monadic encapsulation of effects. This ap...
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Embedded systems are becoming increasingly complex. Besides the additional processing capabilities, they are characterized by high diversity of computational models coexisting in ...
Antonio Carlos Schneider Beck, Mateus B. Rutzig, G...