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Yes in my experience, and from their results, optimizing the combine function (i.e. sample sum, max, min for combining size_a and size_b) is subsumed by optimizing a costmod coefficient like:
size_ab / costmod - (size_a + size_b) * costmod
which is what cotengra does in its hyper-greedy approach. I actually recently added a separate random-greedy optimizer with costmod sampling to the (rust-written) https://github.com/jcmgray/cotengrust, which dramatically reduces the path finding time too.
As a side note I might open a separate issue about potentially interfacing these rust functions.
An interesting paper citing us crossed my desk: https://arxiv.org/pdf/2405.09644
I have not had the chance to dig into, but worth looking through to see if there are additional algorithms to implement.
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