Can mini-batch gradient descent outperform batch gradient descent?
78589
Why mini batch size is better than one single "batch" with all training data?
109966
How does the Adam method of stochastic gradient descent work?
104621
On the hardness of data to learn
157740
Recursive (online) regularised least squares algorithm
118943
Understanding a derivation of bias correction for the Adam optimizer
79882
Explanation of Spikes in training loss vs. iterations with Adam Optimizer
65681
Should training data in each batch size be resample only one time or at each epoch when using mini-batch
149876
Dimensions of Scale (Gamma) and Offset (Beta) in Batch Norm
129280
Neural networks: why do we randomize the training set?
138454
Determining sample size for ML algorithm validation
85497
Parametric vs non-parametric machine learning methods
102459
Why use gradient descent for linear regression, when a closed-form math solution is available?
42302
Use of Holder inequality in gradient estimate for harmonic function.
143614
Dropout: scaling the activation versus inverting the dropout
37027
the relationship between maximizing the likelihood and minimizing the cross-entropy
88139
Why binary crossentropy can be used as the loss function in autoencoders?
16278
Quick Hessian matrix and gradient calculation?