Learning long-term dependencies with gradient descent is difficult
Recurrent neural networks can be used to map input sequences to output sequences, such as for recognition, production or prediction problems. However, practical difficulties hav...
Publications
2 shownThe problem of learning long-term dependencies in recurrent networks
The authors seek to train recurrent neural networks in order to map input sequences to output sequences, for applications in sequence recognition or production. Results are pres...
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 2
- Citations
- 8,343
- Institution
- AT&T (United States)
External Links
Identifiers
- ORCID
- 0000-0001-8371-7450
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.