no code implementations • 15 Mar 2023 • Muhammad Jahanzeb Khan, Rui Hu, Mohammad Sadoghi, Dongfang Zhao
To evaluate this approach, the authors develop a framework called Data-Decoupling Federated Learning (DDFL) and compare it with state-of-the-art FL systems that tightly couple data management and computation.
no code implementations • 1 Feb 2020 • Suyash Gupta, Sajjad Rahnama, Jelle Hellings, Mohammad Sadoghi
Recent developments in blockchain technology have inspired innovative new designs in resilient distributed and database systems.
Databases Distributed, Parallel, and Cluster Computing
no code implementations • 20 Nov 2019 • Suyash Gupta, Sajjad Rahnama, Mohammad Sadoghi
We show that designing such a well-crafted system is possible and illustrate that even if such a system employs a three-phase protocol, it can outperform another system utilizing a single-phase protocol.
Databases Distributed, Parallel, and Cluster Computing
no code implementations • 3 Nov 2019 • Suyash Gupta, Jelle Hellings, Mohammad Sadoghi
At the core of MultiBFT is an approach to continuously order the client-transactions by running several instances of the underlying BFT protocol in parallel.
Databases Distributed, Parallel, and Cluster Computing
no code implementations • 3 Nov 2019 • Suyash Gupta, Jelle Hellings, Sajjad Rahnama, Mohammad Sadoghi
Multi-party data management and blockchain systems require data sharing among participants.
Databases Distributed, Parallel, and Cluster Computing
no code implementations • COLING 2016 • Thien Huu Nguyen, Nicolas Fauceglia, Mariano Rodriguez Muro, Oktie Hassanzadeh, Alfio Massimiliano Gliozzo, Mohammad Sadoghi
Previous studies have highlighted the necessity for entity linking systems to capture the local entity-mention similarities and the global topical coherence.