说明: Abstract Time series often have a temporal hierarchy, with information that is spread out over multiple time scales. Common recurrent neural networks, however, do not explicitly accommodate such a hierarchy, and most research on them has been focusi <weixin_41245916> 上传 | 大小:333kb
说明: James Martens JMARTENS @ CS . TORONTO . EDU Ilya Sutskever ILYA @ CS . UTORONTO . CA University of Toronto, Canada Abstract In this work we resolve the long-outstanding problem of how to effectively train recurrent neu- ral networks (RNNs) on comple <weixin_41245916> 上传 | 大小:295kb