- Linear, logistic and multinomial regularized regression (L1, L2, ElasticNet)
- stochastic gradient descent, FISTA, coordinate descent
- cross validation
- Basic sparse matrix operations
- PCA, SVD
- k-means, k-medoid
Most of these work on both sparse and dense matrices.
MIT, 2016 Istvan Bartha
