Benchmarking the BFGS algorithm on the BBOB-2009 function testbed

By Raymond Ros. 2009

31 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computational Theory and Mathematics, Optimization & Training, 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 Computational Mechanics

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

In Computational Theory and Mathematics

1. Ilya Loshchilov
2. Frank Hutter
3. Holger H. Hoos
4. Kevin Leyton-Brown
5. Aaron Klein
6. Marco F. Huber
7. Marc-André Zöller
8. Katharina Eggensperger

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

In Signal Processing

1. Frank Hutter
2. Ilya Loshchilov

Citations in the corpus

• SGDR: Stochastic Gradient Descent with Warm Restarts (2016, methodology): “Gradient-based optimization algorithms such as BFGS can also perform restarts to deal with multimodal functions (Ros, 2009).”
• SGDR: Stochastic Gradient Descent with Restarts (2016, methodology): “2.2 RESTARTS IN GRADIENT-BASED OPTIMIZATION Gradient-based optimization algorithms such as BFGS also perform restarts to deal with multimodal functions (Ros, 2009).”