Towards Optimal Active Learning for Matrix Factorization in Recommender Systems.
Rasoul KarimiChristoph FreudenthalerAlexandros NanopoulosLars Schmidt-ThiemePublished in: LWA (2013)
Keyphrases
- matrix factorization
- recommender systems
- collaborative filtering
- active learning
- cold start problem
- low rank
- negative matrix factorization
- factorization methods
- data sparsity
- missing data
- nonnegative matrix factorization
- factor analysis
- variational bayesian
- probabilistic matrix factorization
- implicit feedback
- data matrix
- recommendation systems
- stochastic gradient descent
- learning algorithm
- item recommendation
- semi supervised
- latent factor models
- tensor factorization
- least squares
- user profiles
- user preferences
- transfer learning
- supervised learning
- machine learning
- user ratings
- personalized recommendation
- face recognition
- personalized ranking
- random sampling