Hyperparameter Search
Dynamic Algorithm Configuration
Introduced by Biedenkapp et al. in Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic FrameworkDynamic algorithm configuration (DAC) is capable of generalizing over prior optimization approaches, as well as handling optimization of hyperparameters that need to be adjusted over multiple time-steps.
Image Source: Biedenkapp et al.
Source: Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Reinforcement Learning (RL) | 3 | 8.33% |
| Dialogue Act Classification | 3 | 8.33% |
| Domain Adaptation | 2 | 5.56% |
| Image Classification | 1 | 2.78% |
| Self-Supervised Learning | 1 | 2.78% |
| Unsupervised Image Classification | 1 | 2.78% |
| Continual Learning | 1 | 2.78% |
| Adversarial Attack | 1 | 2.78% |
| Retrieval | 1 | 2.78% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
