Papers › Partial Rankings of Optimizers

Partial Rankings of Optimizers

26 Feb 2024arXiv:2402.16565archive 2025-07-28

Julian Rodemann, Hannah Blocher

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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