216 citations · 236 across the 3 of their papers we have counts for
3 papers
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
Muhammad Ammad-ud-din, Elena Ivannikova, Suleiman A. Khan +4
The increasing interest in user privacy is leading to new privacy preserving machine learning paradigms. In the Federated Learning paradigm, a master machine learning model is dist…
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
Luana Micallef, Iiris Sundin, Pekka Marttinen +5
Providing accurate predictions is challenging for machine learning algorithms when the number of features is larger than the number of samples in the data. Prior knowledge can impr…
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis
Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski
The R package GFA provides a full pipeline for factor analysis of multiple data sources that are represented as matrices with co-occurring samples. It allows learning dependencies…