Optimize the given cost function for thetas parameters. Thetas is a vector and cost function will be responsible to transform it into proper matrices.

Cost function will also accept varargs (e.g. a flag to disable calculating gradient, etc)

Stopping conditions is a vector of stopping condition functions used by the optimizer which in turn used by neural networks training function.

If multiple stopping conditions are provided, it will be treated as OR meaning as long as one of the condition is satisfied, training will be stopped (i.e. optimizer is finished)

Will return a map of cost value and the new theta {:cost 1.56 :thetas […]