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19 January 2023, 13:01:39 UTC
Revision 3cfd3e489b9d5f20027663c3fddbd7759c5831f4 authored by Aaron Meurer on 12 December 2018, 22:51:40 UTC, committed by Aaron Meurer on 12 December 2018, 22:51:40 UTC 
Make the parafac mask support sparse friendly
 
This required adding a mask flag to kruskal_to_tensor() and kr() so that the
mask could be absorbed into the calculation in a sparse friendly way. In order
to be sparse friendly, the mask should be a sparse array with a fill value of
1 (True). In other words, the number of missing values should itself be
sparse.

The generic kr() algorithm was rewritten to use a generic outer product, and
kruskal_to_tensor() now uses sum instead of dot (the NumPy kr() just
multiplies the mask).
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Tip revision: 3cfd3e489b9d5f20027663c3fddbd7759c5831f4 authored by Aaron Meurer on 12 December 2018, 22:51:40 UTC
Make the parafac mask support sparse friendly
Tip revision: 3cfd3e4
CHANGELOG.md 
# 0.4.0

- Added TensorFlow backend with Eager execution
- Added CuPy backend
- PyTorch backend updated for PyTorch >= '0.4.0'

# 0.3.0

- Added PyTorch backend

# 0.2.0

- Added MXNet backend

# 0.1.4

- Added Robust Tensor PCA
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