Our new X account is live! Follow @wizwand_team for updates

Ackley

Benchmarks

Task Name	Dataset Name	SOTA Result
Surrogate Modeling	Ackley 4D	Normalized RMSE0.64	16
Function Optimization	Ackley	Avg Max Reward0.993	12
Global Optimization	Ackley01 function	Mean Objective Value1.94	10
Stochastic Lipschitz Optimization	Ackley	Simple Regret0.078	9
Bayesian Optimization	Ackley d=100 synthetic (round 10)	Relative Batch Instantaneous Regret0.137	9
Bayesian Optimization	Ackley d=50 synthetic (round 10)	Relative Batch Instantaneous Regret0.177	9
Bayesian Optimization	Ackley (d=20) synthetic (round 10)	Relative Batch Instantaneous Regret0.219	9
Bayesian Optimization	Ackley d=10 synthetic (round 10)	Relative Batch Instantaneous Regret0.253	9
Bayesian Optimization	Ackley d=2 synthetic (round 10)	Relative Batch Instantaneous Regret0.165	9
Empirical Coverage Estimation	Ackley4	Empirical Coverage (90%)94	7
Bayesian Optimization	Ackley d+1=4	Average Regret2.24	6
Global Optimization	Ackley 1000D (test)	Mean Fitness13.652	5
Bayesian Optimization	Ackley d=2, 10, 20, 50, 100	Relative Batch Instantaneous Regret29.2	5
Function Optimization	Ackley 64	Avg Max Reward-0.0036	5
Global Optimization	Ackley 100d	Mean Final Objective Value0	5
Global Optimization	Ackley 2d	Mean Objective Value0.169	5
Sequential optimization	Ackley Dim 8	AUC0.36	5
Sequential optimization	Ackley Dim 4	AUC0.59	5
Sequential optimization	Ackley Dim 2	AUC83	5
Global Optimization	Ackley 10-dimensional	Final Error0	5
Level Set Estimation	Ackley 200-dimensional	Avg Runtime (min)18	4
Optimization	Ackley	Mean Iterations3.3	3
Level Set Estimation	Ackley 200	Wilcoxon p-value (Random)0.0117	2
Local Optimization	Ackley 10D (test)	Runtime (s)3.36	2
Stochastic Lipschitz Optimization	Ackley-10	Regret9.4	1

Showing 25 of 25 rows