Towards efficient Bayesian Optimization for Big Data

@inproceedings{Klein2015TowardsEB,
  title={Towards efficient Bayesian Optimization for Big Data},
  author={Aaron Klein and Simon Bartels and Stefan Falkner and Philipp Hennig and Frank Hutter},
  year={2015}
}
We present a new Bayesian optimization method, environmental entropy search (EnvES), suited for optimizing the hyperparameters of machine learning algorithms on large datasets. EnvES executes fast algorithm runs on subsets of the data and probabilistically extrapolates their performance to reason about performance on the entire dataset. It considers the dataset size as an additional degree of freedom to choose freely at each step of the optimization, and sets it adaptively to trade off expected… CONTINUE READING
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