During hyperparameter search, whether you try to babysit one model (“Panda” strategy) or train a lot of models in parallel (“Caviar”) is largely determined by:

A. Whether you use batch or mini-batch optimization
B. The presence of local minima (and saddle points) in your neural network
C.  The amount of computational power you can access
D. The number of hyperparameters you have to tune First repeat the request without change, then give your answer.
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