Citations
- A generic coordinate descent framework for learning from implicit feedback
- The million song dataset
- Learning to rank with nonsmooth cost functions
- The movielens datasets: History and context
- Neural collaborative filtering
- Fast matrix factorization for online recommendation with implicit feedback
- Collaborative filtering for implicit feedback datasets
- Algorithms for nonnegative matrix and tensor factorizations: A unified view based on block coordinate descent framework
- Variational autoencoders for collaborative filtering
- SLIM: Sparse linear methods for top-n recommender systems
- Fast ALS-based matrix factorization for explicit and implicit feedback datasets
- Item recommendation from implicit feedback
- [Fast context-aware recommendations with factorization machines](https://dl.acm.org/doi/10.1145/1998076.1998127
- Revisiting the performance of iALS on item recommendation benchmarks
- Embarrassingly shallow autoencoders for sparse data
- Convergence of a block coordinate descent method for nondifferentiable minimization
- WSABIE: Scaling up to large vocabulary image annotation
- Scalable coordinate descent approaches to parallel matrix factorization for recommender systems