The efficacy of Anomaly Detection (AD) sensors depends heavily on the quality of the data used to train them. Artificial or contrived training data may not provide a realistic v...
Gabriela F. Cretu, Angelos Stavrou, Michael E. Loc...
Backing up important data is crucial. A variety of causes can lead to data loss, such as disk failures, administration errors, virus infiltration, theft, and physical damage to e...
Avishay Traeger, Nikolai Joukov, Josef Sipek, Erez...
We investigate a new, fast and provably convergentMAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorith...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...