Sökning: "hierarchical federated learning"

Hittade 4 uppsatser innehållade orden hierarchical federated learning.

1. 1. Fault-Tolerant Over-the-Air Federated Learning with Clustered Aggregation : Using a hierarchical architecture with hybrid digital and analog communication, to deal with byzantine users in Federated Learning over wireless networks.

   Master-uppsats, Linköpings universitet/Kommunikationssystem

   Författare :David Nordlund; [2023]
   Nyckelord :federated learning; aircomp;

   Sammanfattning : Rapid advancements in modern AI applications have placed unprecedented demands on large-scale connectivity and data aggregation. The vision of Internet-of-Things (IoT) is supported by a massive amount of distributed sensors and wireless devices that generate useful data for these applications. LÄS MER

3. 2. Cluster selection for Clustered Federated Learning using Min-wise Independent Permutations and Word Embeddings

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Pulasthi Raveen Bandara Harasgama; [2022]
   Nyckelord :Federated learning; Distributed machine learning; Clustering; Word Embeddings; Federerad inlärning; Distribuerad maskininlärning; Klustring; Ordinbäddningar;

   Sammanfattning : Federated learning is a widely established modern machine learning methodology where training is done directly on the client device with local client data and the local training results are shared to compute a global model. Federated learning emerged as a result of data ownership and the privacy concerns of traditional machine learning methodologies where data is collected and trained at a central location. LÄS MER

4. 3. Federated Learning in Large Scale Networks : Exploring Hierarchical Federated Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Henrik Eriksson; [2020]
   Nyckelord :Federated learning; personalization; time series forecasting; clustering; hierarchical federated learning; model interpolation; Mapper; HierFAvg; base stations; non-IID; LSTM; Federerad inlärning; tidsserieprognostisering; personalisering; kluster; hierarkisk federerad inlärning; modellinterpolation; Mapper; HierFAvg; basstationer;

   Sammanfattning : Federated learning faces a challenge when dealing with highly heterogeneous data and it can sometimes be inadequate to adopt an approach where a single model is trained for usage at all nodes in the network. Different approaches have been investigated to succumb this issue such as adapting the trained model to each node and clustering the nodes in the network and train a different model for each cluster where the data is less heterogeneous. LÄS MER

5. 4. Federated Averaging Deep Q-NetworkA Distributed Deep Reinforcement Learning Algorithm

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Sebastian Backstad; [2018]
   Nyckelord :;

   Sammanfattning : In the telecom sector, there is a huge amount of rich data generated every day. This trend will increase with the launch of 5G networks. Telco companies are interested in analyzing their data to shape and improve their core businesses. LÄS MER