Distributed Computing and Inference for Big Data
L Zhou, Z Gong, P Xiang - Annual Review of Statistics and Its …, 2023 - annualreviews.org
Data are distributed across different sites due to computing facility limitations or data privacy
considerations. Conventional centralized methods—those in which all datasets are stored …
considerations. Conventional centralized methods—those in which all datasets are stored …
Recent methodological advances in federated learning for healthcare
For healthcare datasets, it is often impossible to combine data samples from multiple sites
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …
Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Healthcare
F Camirand Lemyre, S Lévesque, MP Domingue… - medRxiv, 2023 - medrxiv.org
Data from multiple organizations are crucial for advancing learning health systems.
However, ethical, legal, and social concerns may restrict the use of standard statistical …
However, ethical, legal, and social concerns may restrict the use of standard statistical …
[PDF][PDF] FACULTÉ DES SCIENCES UNIVERSITÉ DE SHERBROOKE
D Lévesque - savoirs.usherbrooke.ca
Dans ce mémoire, on exposera des méthodes d'inférence pour modèles linéaires
généralisés (MLG) en présence de données horizontalement partitionnées. Ce type …
généralisés (MLG) en présence de données horizontalement partitionnées. Ce type …