Hello. In paper 3.3 Dymamic Range part,
formula (4)
$$\bar s_k = s_k (1 + \Delta_k) \tag{4}$$
formula (6)
$$\bar i = i + \eta_i^{(k)} \tag{6}$$
but there is sort of different in the code, the $\Delta_k$ and $\eta$ are multiplied by lambda_local and lambda_d respectively which (lambda_local and lambda_d) are assigned [0, 0.25, 0.5, 0.75, 1] in the SSRNET_train.py.
Why are they(lambda_local and lambda_d) exist?
Thank you.
Hello. lambda_local and lambda_d are basically hyperparameters for tuning dynamic indexing and dynamic scaling. I just want to make it more flexible. The final choice for both values is one.
Hello. In paper 3.3 Dymamic Range part, formula (4) $$\bar s_k = s_k (1 + \Delta_k) \tag{4}$$ formula (6) $$\bar i = i + \eta_i^{(k)} \tag{6}$$
but there is sort of different in the code, the $\Delta_k$ and $\eta$ are multiplied by
lambda_local
andlambda_d
respectively which (lambda_local
andlambda_d
) are assigned [0, 0.25, 0.5, 0.75, 1] in the SSRNET_train.py.Why are they(
lambda_local
andlambda_d
) exist? Thank you.