  We present an efficient algorithm for solving fractional programming problems
whose objective functions are the ratio of a low-rank quadratic to a positive
definite quadratic with convex constraints. The proposed algorithm for these
convex-convex problems is based on the Shen-Yu Quadratic Transform which finds
stationary points of concave-convex sum-of-ratios problems. We further use
elements of the algorithm proposed in [arXiv:1802.10192] and the classic
Dinkelbach approach to ensure convergence. We show that our algorithm performs
better than previous algorithms for low-rank problems.
