A broad class of hyperparameter tuning methods rely on being able to specify some amount of resources (iterations, time) to spend training a model. An even broader class of hyperparameter tuning algorithms is possible if models training can be paused and resumed.
We should develop some guidelines on how to do this.
A broad class of hyperparameter tuning methods rely on being able to specify some amount of resources (iterations, time) to spend training a model. An even broader class of hyperparameter tuning algorithms is possible if models training can be paused and resumed.
We should develop some guidelines on how to do this.