Name
Abstract | ||
|---|---|---|
There is a widespread misconception that the delta-rule is in some sense guaranteed to work on networks without hidden units. As previous authors have mentioned, there is no such guarantee for classification tasks. We will begin by presenting explicit counter(cid:173) examples illustrating two different interesting ways in which the delta rule can fail. We go on to provide conditions which do guarantee that gradient descent will successfully train networks without hidden units to perform two-category classification tasks. We discuss the generalization of our ideas to networks with hidden units and to multi(cid:173) category classification tasks. |
Year | Venue | Field |
|---|---|---|
1987 | NIPS | Delta rule,Gradient descent,Computer science,Multicategory,Artificial intelligence,Counterexample,Machine learning |
DocType | Citations | PageRank |
Conference | 15 | 13.83 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ben S Wittner | 1 | 141 | 388.99 |
| J. S. Denker | 2 | 3245 | 2524.81 |