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...
We show how nonlinear embedding algorithms popular for use with shallow semisupervised learning techniques such as kernel methods can be applied to deep multilayer architectures, ...
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
This paper focuses on a technique to empower commercial-off-the-shelf (COTS) systems with an execution environment, and corresponding services, to support realtime and embedded ap...