AutoSimulate: (Quickly) learning synthetic data generation
Simulation is increasingly being used for generating large labelled datasets in many machine learning problems. Recent methods have focused on adjusting simulator parameters with the goal of maximising accuracy on a validation task, usually relying on REINFORCE-like gradient estimators. However thes...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Springer
2020
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