Abstract: Traditional query optimization struggles in distributed and federated database environments. The challenges come from having different types of data sources, network delays, and changing ...

Abstract: This paper proposes a theoretical framework to evaluate and compare the performance of stochastic gradient algorithms for distributed learning in relation to their behavior around local ...