Package: lua-torch-optim (0~20171127-ga5ceed7-1)
Links for lua-torch-optim
Download Source Package lua-torch-optim:
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Numeric Optimization Package for Torch Framework
This package contains several optimization routines and a logger for Torch.
The following algorithms are provided:
* Stochastic Gradient Descent * Averaged Stochastic Gradient Descent * L-BFGS * Congugate Gradients * AdaDelta * AdaGrad * Adam * AdaMax * FISTA with backtracking line search * Nesterov's Accelerated Gradient method * RMSprop * Rprop * CMAESAll these algorithms are designed to support batch optimization as well as stochastic optimization. It's up to the user to construct an objective function that represents the batch, mini-batch, or single sample on which to evaluate the objective.
This package provides also logging and live plotting capabilities via the `optim.Logger()` function. Live logging is essential to monitor the network accuracy and cost function during training and testing, for spotting under- and over-fitting, for early stopping or just for monitoring the health of the current optimisation task.
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