The authors introduce a fractional-order Jacobian matrix differentiation method for Autograd, implement it as FLinear in PyTorch, and claim improved performance on DJI and ETTh1 for fractional orders near 0.9.
Fractional stochastic gradient descent for recommender systems
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Fractional-order Jacobian Matrix Differentiation and Its Application in Artificial Neural Networks
The authors introduce a fractional-order Jacobian matrix differentiation method for Autograd, implement it as FLinear in PyTorch, and claim improved performance on DJI and ETTh1 for fractional orders near 0.9.