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Information Leakage from Data Updates in Machine Learning Models
We validate that two snapshots of the model can result in higher information leakage in comparison to having access to only the updated model.
Optimization Matrix Factorization Recommendation Algorithm Based on Rating Centrality
Matrix factorization (MF) is extensively used to mine the user preference from explicit ratings in recommender systems.
Consistence beats causality in recommender systems
The explosive growth of information challenges people's capability in finding out items fitting to their own interests.
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