BOHB: Robust and Efficient Hyperparameter Optimization at Scale — mentioned by abhgh

Wed, 11 Jul 2018 16:11:22 GMT

You are not doing away with the test/validation set. You are doing away with: 1. grid search - you would now only test for parameters that look promising (based on some criteria). Instead of covering the whole grid, you want to be smart about which points to try out. [1] 2. you might still do grid search but you want to preferentially allocate resources to parameter exploration based on how promising they seem. Hyperband - [2]- is an example. 3. you can do both - you can be smart about picking parameters, but for the ones you pick you can preferentially allocate resources. Ex *Bayesian…

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BOHB: Robust and Efficient Hyperparameter Optimization at Scale · HackerPapers discussions

BOHB: Robust and Efficient Hyperparameter Optimization at Scale — mentioned by abhgh