Why and When Neural Networks Improve Local Approximation in Optimization
cs.LG, math.OC
Submitted: 2026-08-25
Updated: 2026-08-25
Comments: 30 pages, 3 figures, 3 tables. Supplementary material (6 pages) included as an ancillary file. Code and raw results: https://github.com/chengkuobian/neural-surrogates-dfo
Code: https://github.com/chengkuobian/neural-surrogates-dfo
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- The limitation of neural nets for approximation and optimization
- Enhancing finite-difference based derivative-free optimization methods with machine learning
- Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
- On the Relationship between $\Lambda$-poisedness in Derivative-Free Optimization and Outliers in Local Outlier Factor
- Sobolev Training for Neural Networks
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