SVD with Imputation
Naive strategy:
1. estimate values for missing matrix elements (e.g. row or column mean)
2. impute them to create a complete matrix
3. run SVD to compute low rank approximation
This is not a good idea
If we have an incomplete observation, SVD is in general not applicable directly to compute low-rank approximations.