TY - JOUR
T1 - A note on using performance and data profiles for training algorithms
AU - Porcelli, Margherita
AU - Toint, Philippe L.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This article shows how to use performance and data profile benchmarking tools to improve the performance of algorithms. We propose to achieve this goal by defining and approximately solving suitable optimization problems involving the parameters of the algorithm under consideration. Because these problems do not have derivatives and may involve integer variables, we suggest using a mixed-integer derivative-free optimizer for this task. A numerical illustration is presented (using the BFO package), which indicates that the obtained gains are potentially significant.
AB - This article shows how to use performance and data profile benchmarking tools to improve the performance of algorithms. We propose to achieve this goal by defining and approximately solving suitable optimization problems involving the parameters of the algorithm under consideration. Because these problems do not have derivatives and may involve integer variables, we suggest using a mixed-integer derivative-free optimizer for this task. A numerical illustration is presented (using the BFO package), which indicates that the obtained gains are potentially significant.
KW - Algorithmic design
KW - Derivative-free optimization
KW - Hyper-parameters optimization
KW - Trainable codes
UR - http://www.scopus.com/inward/record.url?scp=85065609489&partnerID=8YFLogxK
U2 - 10.1145/3310362
DO - 10.1145/3310362
M3 - Article
AN - SCOPUS:85065609489
VL - 45
JO - ACM Transactions on Mathematical Software
JF - ACM Transactions on Mathematical Software
SN - 0098-3500
IS - 2
M1 - a20
ER -