Long short-term memory

Known as: LSTM, Long short term memory 
Long short-term memory (LSTM) is a recurrent neural network (RNN) architecture (an artificial neural network) proposed in 1997 by Sepp Hochreiter and… (More)
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Papers overview

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Highly Cited
2016
Highly Cited
2016
This paper introduces Grid Long Short-Term Memory, a network of LSTM cells arranged in a multidimensional grid that can be… (More)
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Highly Cited
2016
Highly Cited
2016
Machine reading, the automatic understanding of text, remains a challenging task of great value for NLP applications. We propose… (More)
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Highly Cited
2016
Highly Cited
2016
We propose a novel supervised learning technique for summarizing videos by automatically selecting keyframes or key subshots… (More)
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Highly Cited
2015
Highly Cited
2015
We propose a technique for learning representations of parser states in transitionbased dependency parsers. Our primary… (More)
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Highly Cited
2015
Highly Cited
2015
Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of… (More)
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Highly Cited
2015
Highly Cited
2015
The chain-structured long short-term memory (LSTM) has showed to be effective in a wide range of problems such as speech… (More)
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Highly Cited
2015
Highly Cited
2015
Both Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) have shown improvements over Deep Neural Networks… (More)
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Highly Cited
2014
Highly Cited
2014
Long Short-Term Memory (LSTM) is a specific recurrent neural network (RNN) architecture that was designed to model temporal… (More)
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Highly Cited
2001
Highly Cited
2001
This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM… (More)
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Review
1997
Review
1997
Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of… (More)
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