Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
In this paper, we call the pattern classification problem that consists in assigning a category label to a long audio signal based on its semantic content as Generic Audio Documen...
The Kahn Process Network (KPN) model is a widely used modelof-computation to specify and map streaming applications onto multiprocessor systems-on-chips. In general, KPNs are difï...
We present a general learning-based approach for phrase-level sentiment analysis that adopts an ordinal sentiment scale and is explicitly compositional in nature. Thus, we can mod...
The Unified Modeling Language UML is well-suited for the design of real-time systems. In particular, the design of dynamic system behaviors is supported by interaction diagrams an...