Statements (19)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:author |
gptkb:Shimon_Schocken
Allan Pinkus Moshe Leshno Vladimir Y. Lin |
| gptkbp:citation |
gptkb:universal_approximation_theorem
|
| gptkbp:contribution |
Proved that multilayer feedforward neural networks with a nonpolynomial activation function are universal approximators
|
| gptkbp:doi |
10.1016/S0893-6080(05)80131-5
|
| gptkbp:field |
gptkb:machine_learning
neural networks |
| https://www.w3.org/2000/01/rdf-schema#label |
Leshno et al. (1993)
|
| gptkbp:numberOfIssues |
6
|
| gptkbp:pages |
861-867
|
| gptkbp:publicationYear |
1993
|
| gptkbp:publishedIn |
gptkb:Neural_Networks
|
| gptkbp:title |
Multilayer feedforward networks with a nonpolynomial activation function can approximate any function
|
| gptkbp:volume |
6
|
| gptkbp:bfsParent |
gptkb:Universal_Approximation_Theorem
|
| gptkbp:bfsLayer |
7
|