The goal of this Robot Ontology effort is to develop and begin to populate a neutral knowledge representation (the data structures) capturing relevant information about robots and...
This study addresses the problem of unsupervised visual learning. It examines existing popular model order selection criteria before proposes two novel criteria for improving visu...
Data imputation approaches for robust automatic speech recognition reconstruct noise corrupted spectral information by exploiting prior knowledge of the relationship between targe...
The increasing number of Semantic Web applications that work with ontologies implies an increased need for building ontological knowledge bases. In order to improve ontologies duri...
We present a new class of statistical deanonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. ...