Partial Rankings of Optimizers
Julian Rodemann · Hannah Blocher
2024 Poster
in
Affinity Event: Tiny Papers Poster Session 7
in
Affinity Event: Tiny Papers Poster Session 7
Abstract
We introduce a framework for benchmarking optimizers according to multiple criteria over various test functions. Based on a recently introduced union-free generic depth function for partial orders/rankings, it fully exploits the ordinal information and allows for incomparability. Our method describes the distribution of all partial orders/rankings, avoiding the notorious shortcomings of aggregation. This permits to identify test functions that produce central or outlying rankings of optimizers and to assess the quality of benchmarking suites.
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