Popular gradient-based strategies for optimizing parameters in neural networks.
For a discussion regarding the generalization performance of the solutions found via different optimization strategies, see:
| [1] | Wilson et al. (2017) "The marginal value of adaptive gradient methods in machine learning", Proceedings of the 31st Conference on Neural Information Processing Systems https://arxiv.org/pdf/1705.08292.pdf |
.. autoclass:: numpy_ml.neural_nets.optimizers.optimizers.OptimizerBase
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.. autoclass:: numpy_ml.neural_nets.optimizers.SGD
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.. autoclass:: numpy_ml.neural_nets.optimizers.AdaGrad
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.. autoclass:: numpy_ml.neural_nets.optimizers.Adam
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.. autoclass:: numpy_ml.neural_nets.optimizers.RMSProp
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