| 词条 | Highway network |
| 释义 |
In machine learning, a highway network is an approach to optimizing networks and increasing their depth. Highway networks use learned gating mechanisms to regulate information flow, inspired by Long Short-Term Memory (LSTM) recurrent neural networks. The gating mechanisms allow neural networks to have paths for information to follow across different layers ("information highways").[1][2] Highway networks have been used as part of text sequence labeling[3] and speech recognition[4] tasks. References1. ^{{cite arxiv|last1=Srivastava|first1=Rupesh Kumar|last2=Greff|first2=Klaus|last3=Schmidhuber|first3=Jürgen|title=Highway Networks|eprint=1505.00387|date=2 May 2015|class=cs.LG}} {{compu-ai-stub}}2. ^{{cite journal|last1=Srivastava|first1=Rupesh K|last2=Greff|first2=Klaus|last3=Schmidhuber|first3=Juergen|title=Training Very Deep Networks|journal=Advances in Neural Information Processing Systems 28|date=2015|pages=2377–2385|url=http://papers.nips.cc/paper/5850-training-very-deep-networks|publisher=Curran Associates, Inc.}} 3. ^{{cite arxiv|last1=Liu|first1=Liyuan|last2=Shang|first2=Jingbo|last3=Xu|first3=Frank F.|last4=Ren|first4=Xiang|last5=Gui|first5=Huan|last6=Peng|first6=Jian|last7=Han|first7=Jiawei|title=Empower Sequence Labeling with Task-Aware Neural Language Model|eprint=1709.04109|date=12 September 2017|class=cs.CL}} 4. ^{{cite arxiv|last1=Kurata|first1=Gakuto|last2=Ramabhadran|first2=Bhuvana|last3=Saon|first3=George|last4=Sethy|first4=Abhinav|title=Language Modeling with Highway LSTM|eprint=1709.06436|date=19 September 2017|class=cs.CL}} 1 : Machine learning |
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