  This paper proposes a practical and efficient solution for computing
convolutions using hybrid dealiasing. It offers an alternative to explicit or
implicit dealiasing and includes an optimized hyperparameter tuning algorithm
that uses experience to find the optimal parameters. Machine learning
algorithms and efficient heuristics are also developed to estimate optimal
parameters for larger convolution problems using only small squares/rectangles.
