  We consider the problem of private distributed matrix multiplication under
limited resources. Coded computation has been shown to be an effective solution
in distributed matrix multiplication, both providing privacy against the
workers and boosting the computation speed by efficiently mitigating
stragglers. In this work, we propose the use of recently-introduced bivariate
polynomial codes to further speed up private distributed matrix multiplication
by exploiting the partial work done by the stragglers rather than completely
ignoring them. We show that the proposed approach significantly reduces the
average computation time of private distributed matrix multiplication compared
to its competitors in the literature, while improving the upload communication
cost and the workers' storage efficiency.
