Statements (24)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
hyperparameter optimization algorithm
|
| gptkbp:application |
gptkb:machine_learning
deep learning |
| gptkbp:author |
gptkb:Ameet_Talwalkar
gptkb:Lisha_Li Afshin Rostamizadeh Giulia DeSalvo Kevin Jamieson |
| gptkbp:basedOn |
multi-armed bandit strategy
|
| gptkbp:citation |
2017
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization |
| gptkbp:contrastsWith |
Bayesian optimization
random search |
| gptkbp:developedBy |
gptkb:Lisha_Li
|
| gptkbp:goal |
find optimal hyperparameters with fewer resources
|
| https://www.w3.org/2000/01/rdf-schema#label |
HyperBand
|
| gptkbp:openSource |
gptkb:Optuna
gptkb:Ray_Tune scikit-optimize |
| gptkbp:proposedBy |
efficient hyperparameter search
|
| gptkbp:publishedIn |
International Conference on Learning Representations (ICLR) 2017
|
| gptkbp:uses |
successive halving
|
| gptkbp:bfsParent |
gptkb:Ray_Tune
|
| gptkbp:bfsLayer |
8
|