Decoupled Neural Interfaces using Synthetic Gradients

18 August 2016

Max Jaderberg

Wojciech M. Czarnecki

David Silver

Papers citing "Decoupled Neural Interfaces using Synthetic Gradients"

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Title
Improving Discrete Latent Representations With Differentiable Approximation Bridges Jason Ramapuram Russ Webb DRL 19 9 0 09 May 2019
Contrastive Learning for Lifted Networks Christopher Zach V. Estellers SSL 17 12 0 07 May 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle Dinghuai Zhang Tianyuan Zhang Yiping Lu Zhanxing Zhu Bin Dong AAML 25 357 0 02 May 2019
Embodied Neuromorphic Vision with Event-Driven Random Backpropagation Jacques Kaiser Alexander Friedrich J. C. V. Tieck Daniel Reichard A. Rönnau Emre Neftci Rüdiger Dillmann 11 6 0 09 Apr 2019
Alternating Synthetic and Real Gradients for Neural Language Modeling Fangxin Shang Hao Zhang 18 1 0 27 Feb 2019
Modularity as a Means for Complexity Management in Neural Networks Learning David Castillo-Bolado Cayetano Guerra M. Hernández-Tejera 21 5 0 25 Feb 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 25 199 0 21 Feb 2019
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning Frederik Benzing M. Gauy Asier Mujika A. Martinsson Angelika Steger 23 22 0 11 Feb 2019
Predict Globally, Correct Locally: Parallel-in-Time Optimal Control of Neural Networks P. Parpas Corey Muir OOD 11 12 0 07 Feb 2019
On the Variance of Unbiased Online Recurrent Optimization Tim Cooijmans James Martens 8 14 0 06 Feb 2019
DANTE: Deep AlterNations for Training nEural networks Vaibhav Sinha Sneha Kudugunta Adepu Ravi Sankar Surya Teja Chavali Purushottam Kar V. Balasubramanian 6 3 0 01 Feb 2019
TF-Replicator: Distributed Machine Learning for Researchers P. Buchlovsky David Budden Dominik Grewe Chris Jones John Aslanides ... Aidan Clark Sergio Gomez Colmenarejo Aedan Pope Fabio Viola Dan Belov GNN OffRL AI4CE 37 20 0 01 Feb 2019
Network Parameter Learning Using Nonlinear Transforms, Local Representation Goals and Local Propagation Constraints Dimche Kostadinov Behrooz Razdehi Slava Voloshynovskiy 15 0 0 31 Jan 2019
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets G. Bellec Franz Scherr Elias Hajek Darjan Salaj Robert Legenstein Wolfgang Maass PINN 14 89 0 25 Jan 2019
Self-Supervised Generalisation with Meta Auxiliary Learning Shikun Liu Andrew J. Davison Edward Johns SSL OOD 8 161 0 25 Jan 2019
Decoupled Greedy Learning of CNNs Eugene Belilovsky Michael Eickenberg Edouard Oyallon 8 114 0 23 Jan 2019
Training Neural Networks with Local Error Signals Arild Nøkland L. Eidnes 32 226 0 20 Jan 2019
Credit Assignment Techniques in Stochastic Computation Graphs T. Weber N. Heess Lars Buesing David Silver 21 45 0 07 Jan 2019
Greedy Layerwise Learning Can Scale to ImageNet Eugene Belilovsky Michael Eickenberg Edouard Oyallon 9 180 0 29 Dec 2018
Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE) Jacques Kaiser Hesham Mostafa Emre Neftci 17 23 0 27 Nov 2018
Stable Opponent Shaping in Differentiable Games Alistair Letcher Jakob N. Foerster David Balduzzi Tim Rocktaschel Shimon Whiteson 26 110 0 20 Nov 2018
Towards learning-to-learn B. Lansdell Konrad Paul Kording 23 19 0 01 Nov 2018
Reversible Recurrent Neural Networks M. Mackay Paul Vicol Jimmy Ba Roger C. Grosse 6 52 0 25 Oct 2018
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations Alexander Ororbia A. Mali C. Lee Giles Daniel Kifer 21 63 0 17 Oct 2018
Learning to Perform Local Rewriting for Combinatorial Optimization Xinyun Chen Yuandong Tian NAI OffRL 36 337 0 30 Sep 2018
Backprop-Q: Generalized Backpropagation for Stochastic Computation Graphs Xiaoran Xu Songpeng Zu Yuan Zhang Hanning Zhou Wei Feng BDL 10 4 0 25 Jul 2018
Training Neural Networks Using Features Replay Zhouyuan Huo Bin Gu Heng-Chiao Huang 25 69 0 12 Jul 2018
Guided evolutionary strategies: Augmenting random search with surrogate gradients Niru Maheswaranathan Luke Metz George Tucker Dami Choi Jascha Narain Sohl-Dickstein 22 20 0 26 Jun 2018
Gradient Adversarial Training of Neural Networks Ayan Sinha Zhao Chen Vijay Badrinarayanan Andrew Rabinovich AAML 30 33 0 21 Jun 2018
Massively Parallel Video Networks João Carreira Viorica Patraucean L. Mazaré Andrew Zisserman Simon Osindero 21 42 0 11 Jun 2018
Approximating Real-Time Recurrent Learning with Random Kronecker Factors Asier Mujika Florian Meier Angelika Steger 19 60 0 28 May 2018
Biologically Motivated Algorithms for Propagating Local Target Representations Alexander Ororbia A. Mali 20 87 0 26 May 2018
Breaking the Activation Function Bottleneck through Adaptive Parameterization Sebastian Flennerhag Hujun Yin J. Keane Mark Elliot 19 12 0 22 May 2018
Network Learning with Local Propagation Dimche Kostadinov Behrooz Razeghi Sohrab Ferdowsi Slava Voloshynovskiy 6 0 0 20 May 2018
Local Critic Training of Deep Neural Networks Hojung Lee Jong-Seok Lee 33 8 0 03 May 2018
Decoupled Parallel Backpropagation with Convergence Guarantee Zhouyuan Huo Bin Gu Qian Yang Heng-Chiao Huang 23 97 0 27 Apr 2018
Substitute Teacher Networks: Learning with Almost No Supervision Samuel Albanie James Thewlis Joao F. Henriques 14 2 0 01 Apr 2018
Conducting Credit Assignment by Aligning Local Representations Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles ODL 26 29 0 05 Mar 2018
Learning Longer-term Dependencies in RNNs with Auxiliary Losses Trieu H. Trinh Andrew M. Dai Thang Luong Quoc V. Le 35 179 0 01 Mar 2018
Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning Sanjit Bhat David Lu Albert Kwon S. Devadas AAML 21 190 0 28 Feb 2018
The Mechanics of n-Player Differentiable Games David Balduzzi S. Racanière James Martens Jakob N. Foerster K. Tuyls T. Graepel MLT 21 274 0 15 Feb 2018
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation Shiyu Duan Shujian Yu Yunmei Chen José C. Príncipe 13 16 0 11 Feb 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 33 243 0 07 Feb 2018
Benchmarking Decoupled Neural Interfaces with Synthetic Gradients Ekaba Bisong 11 0 0 22 Dec 2017
Learning to Adapt by Minimizing Discrepancy Alexander Ororbia P. Haffner David Reitter C. Lee Giles AI4TS 21 28 0 30 Nov 2017
Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks Zuozhu Liu Tony Q.S. Quek Shaowei Lin 16 3 0 21 Nov 2017
Deep supervised learning using local errors Hesham Mostafa V. Ramesh Gert Cauwenberghs 27 113 0 17 Nov 2017
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 30 15 0 07 Nov 2017
Maximum Principle Based Algorithms for Deep Learning Qianxiao Li Long Chen Cheng Tai E. Weinan 15 221 0 26 Oct 2017
Training Spiking Neural Networks for Cognitive Tasks: A Versatile Framework Compatible to Various Temporal Codes Chaofei Hong 13 0 0 02 Sep 2017