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A black-box optimization benchmark tool

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Kurobako has `evaluate` subcommand that evaluates a problem at a given set of params. However, when we want to repeatedly evaluate different sets of params and the problem needs to...

Currently, the standard input and output are used to communicate with external program problems and solvers but it turned out that it's not a good design. Because many Python libraries...

contribution-welcome
needs-discussion

Currently, debugging subprocesses run by kurobako is rather painful. There can be multiple possible improvements. * We could show that "During study <study setting>, subprocess <id> finished with an error...

contribution-welcome

See https://github.com/optuna/kurobako/pull/39#discussion_r657630351 Ref. https://hub.docker.com/r/sile/kurobako, https://hub.docker.com/u/optuna

It may be useful to support metrics that aren't visible to solvers but can be used in the ranking evaluation or plotting phases.

Hi! I would like to use the following performance metrics to validate the hyperparameter optimization algorithms with `kurobako`. - The number of budgets to reach the X% point of the...

[Optuna v3.0](https://github.com/optuna/optuna/releases/tag/v3.0.0) has been released, and it deprecated the old distributions and introduced the new distributions. We should replace the old definitions with new ones. ## What we should change....

contribution-welcome

Bumps [memoffset](https://github.com/Gilnaa/memoffset) from 0.6.1 to 0.6.5. Commits 01e2e42 v0.6.5 fd81a21 Merge pull request #63 from yvt/fix-nightly 4248395 Remove #![feature(const_raw_ptr_deref)] 4c71bed Remove #![feature(const_maybe_uninit_as_ptr)] b14262b Merge pull request #62 from matklad/idioms d41cc25...

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