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| data_mining:neural_network:gradient_descent [2018/05/12 20:17] – [Learning rate decay] phreazer | data_mining:neural_network:gradient_descent [2018/05/12 20:21] (current) – [Learning rate decay] phreazer | ||
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| + | ===== Saddle points ===== | ||
| + | In high-dimensional spaces it's more likely to end up at a saddle point (than in local optima). E.g. 20000 parameter, highly unlikely that it's a local minimum you get stuck. Plateus make learning slow. | ||