tree: 6c660fa83d3e635b478d007552ea25c0ee8fc599 [path history] [tgz]
  1. data.py
  2. model.py
  3. README.md
  4. train.py
example/sparse/matrix_factorization/README.md

Matrix Factorization w/ Sparse Embedding

The example demonstrates the basic usage of the SparseEmbedding operator in MXNet, adapted based on @leopd's recommender examples. The operator is available on both CPU and GPU. This is for demonstration purpose only.

  • python train.py
  • To compare the training speed with (dense) Embedding, run python train.py --use-dense
  • To run the example on the GPU, run python train.py --use-gpu