Command line options

Name	Shortcut	Full argument	Default	Description
Algorithm	-a	–algorithms	baxus	The algorithm to run. Has to be from baxus, embedded_turbo_target_dim, embedded_turbo_effective_dim, embedded_turbo_2_effective_dim, random_search
Function	-f	–functions	None	One ore several test functions. Has to be from hartmann6, branin2, rosenbrock5, rosenbrock10, ackley, rosenbrock, levy, dixonprice, griewank, michalewicz, rastrigin, svm, lasso-high, lasso-dna, lasso-high, lasso-medium, lasso-leukemia, lasso-rcv1, lasso-breastcancer, lasso-diabetes, lasso-simple, lasso-hard, mopta08, hartmann6in1000_rotated, shiftedackley10.
Input dimensionality	-id	–input-dim	100	Input dimensionality of the function. This is overriden when the function has a fixed dimensionality.
Target dimensionality	-td	–target-dim	10	(Initial) target dimensionality of the function. Whether initial or not depends on the algorithm. Initial for AdaTheSBO-1 and AdaTheSBO-m as they adapt the target dimensionality.
Acquisition function	None	–acquisition-function	ts	Either ts (Thompson sampling) or ei (Expected improvement)
Embedding type	None	–embedding-type	baxus	Either baxus (for the BAxUS embedding) or hesbo (for the HeSBO embedding)
Adjust initial target dimensionality	None	–adjust-initial-target-dimension	not set	Whether to adjust the initial target dimensionality as described in the BAxUS paper.
Number of initial samples	-n	–n-init	None (set to target dimensionality + 1 if not set)	Number of DOE samples.
Number of repetitions	-r	–num-repetitions	1	Number of repetitions of the run.
Number of evaluations	-m	–max-evals	300	Number of evaluations. Cma-ES might use a few more.
Initial baselength	-l	–initial-baselength	0.8	The initial base length of the trust region (default value is as in the TuRBO paper).
Minimum baselength	-lmin	–min-baselength	0.5^7	The minimum base length a trust region is allowed to obtain (default value is as in the TuRBO paper).
Maximum baselength	-l_max	–max-baselength	1.6	The maximum base length a trust region is allowed to obtain (default value is as in the TuRBO paper).
Noise standard deviation	None	–noise-std	0	The standard deviation of the noise. Whether this is used or not depends on the benchmark. It is generally only recognized for synthetic benchmarks like Branin2 but also for the synthetic Lasso versions.
Results directory	None	–results-dir	results	The directory to which the results are written. Relative to the path from which the run was started.
Run description	None	–run-description	None	Short description that will be added to the run directory
MLE multistart samples	None	–multistart-samples	100	Number of multistart samples for the MLE GD optimization. Samples will be drawn from latin hypercube
Multistarts after sampling	None	–multistart-after-sample	10	Only recognized for ‘–mle-optimization sample-and-choose-best’. Number of multi-start gradient descent optimization out of the --multistart-samples best ones.
MLE optimization method	None	–mle-optimization	sample-and-choose-best	Either multistart-gd or sample-and-choose-best.
Number of MLE gradient updates	None	–mle-training-steps	50	Number of GD steps in MLE maximization.
Budget until input dimensionality	None	–budget-until-input-dim	0	The budget after which BAxUS will roughly reach the input dimensionality (see paper for details). If 0: this setting is ignored
Verbose mode	-v	–verbose	not set	Whether to print verbose messages