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Unbiased Online Recurrent Optimization
v1v2v3 (latest)

Unbiased Online Recurrent Optimization

International Conference on Learning Representations (ICLR), 2017
16 February 2017
Corentin Tallec
Yann Ollivier
ArXiv (abs)PDFHTML

Papers citing "Unbiased Online Recurrent Optimization"

14 / 64 papers shown
Adaptively Truncating Backpropagation Through Time to Control Gradient
  Bias
Adaptively Truncating Backpropagation Through Time to Control Gradient BiasConference on Uncertainty in Artificial Intelligence (UAI), 2019
Christopher Aicher
N. Foti
E. Fox
MQ
211
37
0
17 May 2019
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed
  Self-Feedback Improves Accuracy and Stability
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability
Ziming Zhang
Anil Kag
Alan Sullivan
Venkatesh Saligrama
114
6
0
02 Mar 2019
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning
Optimal Kronecker-Sum Approximation of Real Time Recurrent LearningInternational Conference on Machine Learning (ICML), 2019
Frederik Benzing
M. Gauy
Asier Mujika
A. Martinsson
Angelika Steger
240
28
0
11 Feb 2019
On the Variance of Unbiased Online Recurrent Optimization
On the Variance of Unbiased Online Recurrent Optimization
Tim Cooijmans
James Martens
188
14
0
06 Feb 2019
Continual Learning of Recurrent Neural Networks by Locally Aligning
  Distributed Representations
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations
Alexander Ororbia
A. Mali
C. Lee Giles
Daniel Kifer
331
71
0
17 Oct 2018
General Value Function Networks
General Value Function NetworksJournal of Artificial Intelligence Research (JAIR), 2018
M. Schlegel
Andrew Jacobsen
Zaheer Abbas
Andrew Patterson
Adam White
Martha White
289
30
0
18 Jul 2018
Approximating Real-Time Recurrent Learning with Random Kronecker Factors
Approximating Real-Time Recurrent Learning with Random Kronecker Factors
Asier Mujika
Florian Meier
Angelika Steger
273
64
0
28 May 2018
Low-pass Recurrent Neural Networks - A memory architecture for
  longer-term correlation discovery
Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery
T. Stepleton
Razvan Pascanu
Will Dabney
Siddhant M. Jayakumar
Hubert Soyer
Rémi Munos
144
4
0
13 May 2018
Learning to Adapt by Minimizing Discrepancy
Learning to Adapt by Minimizing Discrepancy
Alexander Ororbia
P. Haffner
David Reitter
C. Lee Giles
AI4TS
145
30
0
30 Nov 2017
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent
  Networks
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks
Nan Rosemary Ke
Anirudh Goyal
O. Bilaniuk
Jonathan Binas
Laurent Charlin
C. Pal
Yoshua Bengio
148
15
0
07 Nov 2017
Unbiasing Truncated Backpropagation Through Time
Unbiasing Truncated Backpropagation Through Time
Corentin Tallec
Yann Ollivier
204
83
0
23 May 2017
Online Natural Gradient as a Kalman Filter
Online Natural Gradient as a Kalman Filter
Yann Ollivier
302
72
0
01 Mar 2017
Decoupled Neural Interfaces using Synthetic Gradients
Decoupled Neural Interfaces using Synthetic GradientsInternational Conference on Machine Learning (ICML), 2016
Max Jaderberg
Wojciech M. Czarnecki
Simon Osindero
Oriol Vinyals
Alex Graves
David Silver
Koray Kavukcuoglu
288
385
0
18 Aug 2016
Equilibrium Propagation: Bridging the Gap Between Energy-Based Models
  and Backpropagation
Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation
B. Scellier
Yoshua Bengio
380
568
0
16 Feb 2016
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