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Found 6 papers, 1 papers with code
A Payload Optimization Method for Federated Recommender Systems
We introduce the payload optimization method for federated recommender systems (FRS).
Federated Multi-view Matrix Factorization for Personalized Recommendations
We introduce the federated multi-view matrix factorization method that extends the federated learning framework to matrix factorization with multiple data sources.
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
In the Federated Learning paradigm, a master machine learning model is distributed to user clients, the clients use their locally stored data and model for both inference and calculating model updates.
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
The main component of our approach is a user model that models the domain expert's knowledge of the relevance of different features for a prediction task.
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization
We demonstrate that pathway-response associations can be learned by the proposed model for the well known EGFR and MEK inhibitors.
Regression with n$\to$1 by Expert Knowledge Elicitation
We consider regression under the "extremely small $n$ large $p$" condition, where the number of samples $n$ is so small compared to the dimensionality $p$ that predictors cannot be estimated without prior knowledge.
