We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Abstract. We present techniques that enable source-level debugging for multiple languages at the cost of only modest programming effort. The key idea is to avoid letting debugging ...
This paper introduces two novel beamforming algorithms, namely the Region Constrained and Multiple Correlated Source Model beamformers, designed to localize and to reconstruct hig...
In this paper, a framework for building an overall Zero-Latency Data Warehouse system (ZLDWH) is provided. Such a ZLDWH requires tasks such as data changes detection, continuous l...