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Found 6 papers, 0 papers with code
Comparative Evaluation of Data Decoupling Techniques for Federated Machine Learning with Database as a Service
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.
ResilientDB: Global Scale Resilient Blockchain Fabric
Recent developments in blockchain technology have inspired innovative new designs in resilient distributed and database systems.
Databases Distributed, Parallel, and Cluster Computing
Permissioned Blockchain Through the Looking Glass: Architectural and Implementation Lessons Learned
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
Scaling Blockchain Databases through Parallel Resilient Consensus Paradigm
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
Proof-of-Execution: Reaching Consensus through Fault-Tolerant Speculation
Multi-party data management and blockchain systems require data sharing among participants.
Databases Distributed, Parallel, and Cluster Computing
Joint Learning of Local and Global Features for Entity Linking via Neural Networks
Previous studies have highlighted the necessity for entity linking systems to capture the local entity-mention similarities and the global topical coherence.
