DeepLearning.AI course on using Flower architecture for federated learning. - Pranav-JJ/Intro-to-Federated-Learning
Now you are ready for deploying the FL pipeline using K8s. We will be using K8s deployments to create K8s pods that will use a K8s service for communications. Each pod represents a FL actor with a main pod that will act as a FL server. The proposed architecture is depicted in the figur...
3. Kubeflower: Privacy-preserving cloud-native federated learning Kubernetes (K8s) provides an infrastructure that not only can simplify FL model deployment and scaling but also can offer flexible, and cost-effective execution of FL systems in cloud-native environments. However, it also introduces ch...
Based on an event-driven architecture, FederatedScope integrates rich collections of functionalities to satisfy the burgeoning demands from federated learning, and aims to build up an easy-to-use platform for promoting learning safely and effectively. Keywords: Federated learning, Event-...
FederatedScope is a comprehensive federated learning platform that provides convenient usage and flexible customization for various federated learning tasks in both academia and industry. Based on an event-driven architecture, FederatedScope integrates rich collections of functionalities to satisf...
In this project, we aim to augment a Ring Learning With Errors (RLWE) scheme and integrate it into our federated learning architecture to enable multi-key HE. RLWE is a mathematical problem that leverages lattices over polynomial rings to create an encryption scheme. We will delve into a ...
Propose a segmentation technique using deep learning and a saliency map for tumor detection. The residual block will be added in the deep learning model, which can aid in better learning for the detection process. Develop a fusion-based deep learning architecture with Bayesian optimization-based hyp...
Here, adaptation to embedded camera devices was accomplished using SRNet20 generated by a Neural Architecture Search (NAS). Because of security, SRNet20 was trained in federated learning. The DRFL network provided better performance, but the model was not capable of identifying the long-distance ...
FATE provides Standalone runtime architecture for developers. It can help developers quickly test FATE. Standalone support two types of deployment: Docker version and Manual version. Please refer to Standalone deployment guide: standalone-deploy Cluster FATE also provides a distributed runtime architect...
federated learning tasks in both academia and industry. Based on an event-driven architecture,FederatedScopeintegrates rich collections of functionalities to satisfy the burgeoning demands from federated learning, and aims to build up an easy-to-use platform for promoting learning safely and effectively....