Machine Learning, Gradient Descent, Optimization, Deep Learning, Artificial Intelligence.
RMSProp : 0.49 at [-16.2053, -86.8066] AdaDelta : 0.49 at [-16.2967, -86.8238] AdaGrad : 0.49 at [-16.2966, -86.8238] AdamW : 0.49 at [-7.1560, -85.5803] Conclusion With these toy functions, we were able to understand the inner mechanics of Gradient descents and where they perform well.