We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Most quality and software process improvement frameworks emphasize written (i.e. formal) documentation to convey recommended work practices. However, there is considerable skeptic...
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
This paper concerns the problem of identity management in modern Web-2.0-based mashup applications. Identity management supports convenient access to information when mashups are ...