tensorr provides methods to manipulate and store sparse tensors. Tensors are multi-dimensional generalizations of matrices (two dimensional) and vectors (one dimensional).
It has three main goals:
Provide an efficient format to store sparse tensors in R.
Provide standard tensor operations such as multiplication and unfolding.
Provide standard tensor decomposition techniques such as CP and Tucker.
Many of the dense and sparse implementation ideas were adapted from
B. W. Bader and T. G. Kolda. Algorithm 862: MATLAB tensor classes for fast algorithm prototyping, ACM Transactions on Mathematical Software 32(4):635-653, December 2006.
B. W. Bader and T. G. Kolda. Efficient MATLAB computations with sparse and factored tensors, SIAM Journal on Scientific Computing 30(1):205-231, December 2007.
For a review on tensors, see
T. G. Kolda and B. W. Bader, Tensor Decompositions and Applications, SIAM Review 51(3):455-500, September 2009