For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples fro...
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the datab...
We consider the problem of estimating the covariance matrix of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly ...
—In network measurement systems, packet sampling techniques are usually adopted to reduce the overall amount of data to collect and process. Being based on a subset of packets, t...
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant " space, ...
Sathish Ramani, Dimitri Van De Ville, Michael Unse...