DONE

For other uses, see Done.

The Data-based Online Nonlinear Extremumseeker (DONE) algorithm is a black-box optimization algorithm. DONE models the unknown cost function and attempts to find an optimum of the underlying function. The DONE algorithm is suitable for optimizing costly and noisy functions and does not require derivatives. An advantage of DONE over similar algorithms, such as Bayesian optimization, is that the computational cost per iteration is independent of the number of function evaluations.

Methods

The DONE algorithm was first proposed by Hans Verstraete and Sander Wahls in 2015.[1] The algorithm fits a surrogate model based on random Fourier features[2] and then uses a well-known L-BFGS algorithm to find an optimum of the surrogate model.

Applications

DONE was first demonstrated for maximizing the signal in optical coherence tomography measurements, but has since then been applied to various other applications. For example, it was used to help extending the field of view in light sheet fluorescence microscopy.[3]

References

  1. ^ Hans R. G. W. Verstraete, Sander Wahls, Jeroen Kalkman, Michel Verhaegen: Model-based sensor-less wavefront aberration correction in optical coherence tomography, Opt. Lett. 40, 5722-5725 (2015)
  2. ^ Ali Rahimi, Benjamin Recht: Random features for large-scale kernel machines, Advances in neural information processing systems, pp. 1177-1184 (2007)
  3. ^ Dean Wilding, Paolo Pozzi, Oleg Soloviev, Gleb Vdovin, Colin J. Sheppard, Michel Verhaegen: Pupil filters for extending the field-of-view in light-sheet microscopy, Optics letters 41, no. 6 (2016): 1205-1208
Stub icon

This algorithms or data structures-related article is a stub. You can help Wikipedia by adding missing information.

Content Disclaimer

Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.

  1. The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
  2. There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
  3. It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
  4. Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
  5. Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.