The Parallel Bayesian Optimization Algorithm

By Jiri Ocenasek, Josef Schwarz. 2000

63 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Colin White
2. Yash Savani
3. Willie Neiswanger
4. Mark Hauschild
5. Martin Pelikan
6. Sam Nolen
7. Martin Zaefferer
8. Thomas Bartz-Beielstein

In Signal Processing

1. Yash Savani
2. Colin White
3. Willie Neiswanger

Citations in the corpus

• BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search (2019, methodology): “e previous work on using neural network models in Bayesian optimization [39, 40], applied to the task of hyperparameter optimization. There are also techniques for parallelizing Bayesian optimization [10,16,33]. Predicting neural network accuracy. There are several approaches for predicting the vali”
• An introduction and survey of estimation of distribution algorithms (2011, background): “Typically, learning the model structure is much more complex than learning the parameters [145,42].”