Tight convex relaxations for sparse matrix factorization.
Emile RichardGuillaume ObozinskiJean-Philippe VertPublished in: NIPS (2014)
Keyphrases
- matrix factorization
- convex relaxation
- tensor factorization
- collaborative filtering
- convex optimization
- latent factors
- low rank
- negative matrix factorization
- factorization methods
- recommender systems
- high dimensional
- multi label
- missing data
- nonnegative matrix factorization
- globally optimal
- multistage
- optimization methods
- sparsity constraints
- multiple kernel learning
- unsupervised learning
- graph cuts
- machine learning