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We present a framework for compactly summarizing many recent results in efficient and/or biologically plausible online training of recurrent neural networks (RNN).
Backpropagation through time: what it does and how to do it
Paul J Werbos et al · 1990
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Reservoir computing approaches to recurrent neural network training
Mantas Lukoševičius and Herbert Jaeger · 2009
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Recurrent neural network based language model
Tomáš Mikolov, Martin Karafiát, Lukáš Burget, Jan Černockỳ, and Sanjeev Khudanpur · 2010
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The mnist database of handwritten digit images for machine learning research [best of the web]
Li Deng · 2012
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Lecture 6.5—RmsProp: Divide the gradient by a running average of its recent magnitude
T. Tieleman and G. Hinton · 2012
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Generating sequences with recurrent neural networks
Alex Graves · 2013
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Describing multimedia content using attention-based encoder-decoder networks
Kyunghyun Cho, Aaron Courville, and Yoshua Bengio · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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End-to-end attention-based large vocabulary speech recognition
Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, and Yoshua Bengio · 2016
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Hybrid computing using a neural network with dynamic external memory
Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio Gómez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou, et al · 2016
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Random synaptic feedback weights support error backpropagation for deep learning
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, and Colin J Akerman · 2016
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Understanding synthetic gradients and decoupled neural interfaces
Wojciech Marian Czarnecki, Grzegorz Swirszcz, Max Jaderberg, Simon Osindero, Oriol Vinyals, and Koray Kavukcuoglu · 2017
Cited alongside, same era.
Online learning of recurrent neural architectures by locally aligning distributed representations
Alexander Ororbia, Ankur Mali, C Lee Giles, and Daniel Kifer · 2018
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Recurrent neural networks in tensorflow 1
Silviu Pitis · 2018
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Dendritic cortical microcircuits approximate the backpropagation algorithm
João Sacramento, Rui Ponte Costa, Yoshua Bengio, and Walter Senn · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Optimal kronecker-sum approximation of real time recurrent learning
Frederik Benzing, Marcelo Matheus Gauy, Asier Mujika, Anders Martinsson, and Angelika Steger · 2019
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Towards deep learning with segregated dendrites
Jordan Guerguiev, Timothy P Lillicrap, and Blake A Richards · 2017
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Decoupled neural interfaces using synthetic gradients
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, and Koray Kavukcuoglu · 2017
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Learning to adapt by minimizing discrepancy
II Ororbia, G Alexander, Patrick Haffner, David Reitter, and C Lee Giles · 2017
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Unbiased online recurrent optimization
Corentin Tallec and Yann Ollivier · 2017
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A learning algorithm for continually running fully recurrent neural networks
Ronald J Williams and David Zipser · 2017
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Approximating real-time recurrent learning with random kronecker factors
Asier Mujika, Florian Meier, and Angelika Steger · 2018
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Tim Cooijmans and James Martens · 2019
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Backpropagation through time and the brain
Timothy P Lillicrap and Adam Santoro · 2019
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Using local plasticity rules to train recurrent neural networks
Owen Marschall, Kyunghyun Cho, and Cristina Savin · 2019
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Local online learning in recurrent networks with random feedback
James M Murray · 2019
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Kernel RNN learning (keRNL)
Christopher Roth, Ingmar Kanitscheider, and Ila Fiete · 2019
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