Jun 2, 2021 · The system, named FedNCF, enables learning without requiring users to disclose or transmit their raw data. Data localization preserves data ...
Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system.
This paper extends the Neural Collaborative Filtering (NCF) method using a federated setting and proposes a privacy-preserving federated recommender system ...
The system, named FedNCF, enables learning without requiring users to disclose or transmit their raw data. Data localization preserves data privacy and complies ...
Apr 22, 2022 · The system, named FedNCF, enables learning without requiring users to disclose or transmit their raw data. Data localization preserves data ...
Jun 2, 2021 · In this work, we present a federated version of the state-of-the-art. Neural Collaborative Filtering (NCF) approach for item recommen- dations.
May 11, 2024 · FL is a distributed machine learning approach allowing multiple entities to collaboratively train a model without sharing their raw data, ...
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In this thesis a number of models for recommender systems are explored, all using collaborative filtering to produce their recommendations.
This paper extends the Neural Collaborative Filtering (NCF) method using a federated setting and proposes a privacy-preserving federated ...
Federated recommendation system based on neural collaborative filtering [1]. Implementation is done using both Tensorflow/Keras and PyTorch frameworks.
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