Statements (22)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:mathematical_concept
|
| gptkbp:appliesTo |
search algorithms
machine learning algorithms optimization algorithms |
| gptkbp:citation |
gptkb:No_Free_Lunch_Theorems_for_Optimization
|
| gptkbp:field |
gptkb:machine_learning
optimization computational theory |
| gptkbp:formedBy |
gptkb:David_Wolpert
gptkb:William_G._Macready |
| gptkbp:implies |
Algorithm performance is problem-dependent.
No single algorithm is best for all problems. |
| gptkbp:publishedIn |
gptkb:IEEE_Transactions_on_Evolutionary_Computation
|
| gptkbp:relatedConcept |
gptkb:universal_approximation_theorem
computational complexity algorithmic bias inductive bias |
| gptkbp:sentence |
No optimization algorithm is universally better than others across all possible problems.
|
| gptkbp:yearProposed |
1996
|
| gptkbp:bfsParent |
gptkb:There’s_No_Such_Thing_as_a_Free_Lunch
|
| gptkbp:bfsLayer |
6
|
| https://www.w3.org/2000/01/rdf-schema#label |
no free lunch theorem
|