Adaptive nested optimization scheme for multidimensional global search

By Victor P. Gergel, Vladimir A. Grishagin, Alexander Gergel. 2015

47 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Numerical Analysis

How researchers see this paper

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

In Aerospace Engineering

1. Ruslan Israfilov
2. Marta Z. Kwiatkowska
3. Yaroslav D. Sergeyev
4. Xiaowei Huang
5. Wenjie Ruan
6. Vladimir A. Grishagin

In Computer Networks and Communications

1. Ruslan Israfilov
2. Marta Z. Kwiatkowska
3. Yaroslav D. Sergeyev
4. Xiaowei Huang
5. Wenjie Ruan
6. Vladimir A. Grishagin

In Numerical Analysis

1. Marta Z. Kwiatkowska
2. Xiaowei Huang
3. Wenjie Ruan
4. Ruslan Israfilov
5. Yaroslav D. Sergeyev
6. Vladimir A. Grishagin

Citations in the corpus

• Reachability Analysis of Deep Neural Networks with Provable Guarantees (2018, methodology): “To handle the high-dimensionality of DNNs, our approach is inspired by the idea of adaptive nested optimisation in [Gergel et al., 2016], with significant differences in the detailed algorithm and convergence proof.”
• Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes (2018, methodology): “This idea is realized in the adaptive nested optimization scheme proposed in the paper [38] containing a detailed algorithmic description of the adaptive scheme.”