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A note on using performance and data profiles for training algorithms

Margherita Porcelli (margherita.porcelli***at***unifi.it)
Philippe L. Toint (philippe.toint***at***unamur.be)

Abstract: It is shown how to use the performance and data profile benchmarking tools to improve algorithms' performance. An illustration for the BFO derivative-free optimizer suggests that the obtained gains are potentially significant.

Keywords: algorithmic design, algorithms' training, trainable codes, derivative-free optimization

Category 1: Nonlinear Optimization

Category 2: Optimization Software and Modeling Systems (Optimization Software Benchmark )

Category 3: Other Topics (Optimization of Simulated Systems )

Citation: ACM Transactions on Mathematical Software, 45:2 (2019), Article 20.

Download: [PDF]

Entry Submitted: 11/26/2017
Entry Accepted: 11/26/2017
Entry Last Modified: 04/23/2019

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