Niching the CMA-ES via nearest-better clustering

By Mike Preuss. 2010

124 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Hardware and Architecture, Optimization & Training

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. Frank Hutter
2. Ilya Loshchilov
3. Quoc V. Le
4. Dan Hendrycks
5. Xuanyi Dong
6. Christoph Feichtenhofer
7. Ronghang Hu
8. Yi Yang

In Hardware and Architecture

1. Frank Hutter
2. Ilya Loshchilov

In Optimization & Training

1. Frank Hutter
2. Ilya Loshchilov
3. Ronghang Hu
4. Dan Hendrycks
5. Quoc V. Le
6. Laurence Aitchison
7. Christoph Feichtenhofer
8. Michael Auli

Citations in the corpus

• SGDR: Stochastic Gradient Descent with Warm Restarts (2016, methodology): “However, these methods usually work only for relatively small search spaces, e.g., n 10 , and do not scale up due to the curse of dimensionality (Preuss, 2010).”
• SGDR: Stochastic Gradient Descent with Restarts (2016, methodology): “However, these methods usually work only for relatively small search spaces, e.g., n 10, and do not scale up due to the curse of dimensionality (Preuss, 2010).”