A survey on the use of Federated Learning in Privacy-Preserving Recommender Systems
In the age of information overload, recommender systems have emerged as essential tools,
assisting users in decision-making processes by offering personalized suggestions …
assisting users in decision-making processes by offering personalized suggestions …
Federated training of dual encoding models on small non-iid client datasets
Dual encoding models that encode a pair of inputs are widely used for representation
learning. Many approaches train dual encoding models by maximizing agreement between …
learning. Many approaches train dual encoding models by maximizing agreement between …
Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation
H Zhang, H Li, J Chen, S Cui, K Yan… - arxiv preprint arxiv …, 2024 - arxiv.org
Federated recommendation aims to collect global knowledge by aggregating local models
from massive devices, to provide recommendations while ensuring privacy. Current methods …
from massive devices, to provide recommendations while ensuring privacy. Current methods …
Robust Convergence in Federated Learning through Label-wise Clustering
H Lee, Y Liu, D Kim, Y Li - arxiv preprint arxiv:2112.14244, 2021 - arxiv.org
Non-IID dataset and heterogeneous environment of the local clients are regarded as a major
issue in Federated Learning (FL), causing a downturn in the convergence without achieving …
issue in Federated Learning (FL), causing a downturn in the convergence without achieving …