Statements (22)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:mathematical_concept
|
| gptkbp:alsoKnownAs |
gptkb:NFL_theorem
|
| gptkbp:appliesTo |
search algorithms
machine learning algorithms optimization algorithms |
| gptkbp:field |
gptkb:machine_learning
gptkb:mathematics optimization |
| gptkbp:formedBy |
gptkb:David_Wolpert
gptkb:William_G._Macready |
| gptkbp:influenced |
gptkb:evolutionary_computation
theoretical machine learning |
| gptkbp:publishedIn |
gptkb:IEEE_Transactions_on_Evolutionary_Computation
|
| gptkbp:relatedConcept |
gptkb:universal_approximation_theorem
algorithmic bias computational learning theory inductive bias |
| gptkbp:sentence |
No optimization algorithm is universally better than others when performance is averaged over all possible problems.
|
| gptkbp:yearProposed |
1996
|
| gptkbp:bfsParent |
gptkb:David_Wolpert
|
| gptkbp:bfsLayer |
8
|
| https://www.w3.org/2000/01/rdf-schema#label |
No Free Lunch Theorem
|