![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Chapter and Conference Paper
An Optimal Relationship-Based Partitioning of Large Datasets
Modern adaptive applications utilize multiprocessor systems for efficient processing of large datasets where initial and dynamic partitioning of large datasets is necessary to obtain an optimal load balancing ...
-
Chapter and Conference Paper
Flexible Scheduling of Transactional Memory on Trees
We study the efficiency of executing transactions in a distributed transactional memory system. The system is modeled as a wired network with the topology of a tree. Contrary to previous approaches, we allow t...
-
Chapter and Conference Paper
Correct Orchestration of Federated Learning Generic Algorithms: Formalisation and Verification in CSP
Federated learning (FL) is a machine learning setting where clients keep the training data decentralised and collaboratively train a model either under the coordination of a central server (centralised FL) or ...
-
Chapter and Conference Paper
A Federated Learning Algorithms Development Paradigm
At present many distributed and decentralized frameworks for federated learning algorithms are already available. However, development of such a framework targeting smart Internet of Things in edge systems is ...