Reference Summary: Gradient Descent and its variants are very useful, but there exists an entire other Stochastic gradient-based methods are the state-of-the-art in large-scale
Efficient Second Order Optimization For Machine Learning -
Gradient Descent and its variants are very useful, but there exists an entire other Stochastic gradient-based methods are the state-of-the-art in large-scale
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- Gradient Descent and its variants are very useful, but there exists an entire other
- Stochastic gradient-based methods are the state-of-the-art in large-scale
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