Direct Feedback Alignment Provides Learning in Deep Neural Networks

6 September 2016

Papers citing "Direct Feedback Alignment Provides Learning in Deep Neural Networks"

50 / 248 papers shown

Title
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence Charlotte Frenkel D. Bol Giacomo Indiveri 36 34 0 02 Jun 2021
In-Hardware Learning of Multilayer Spiking Neural Networks on a Neuromorphic Processor Amar Shrestha Haowen Fang D. Rider Zaidao Mei Qinru Qiu 38 26 0 08 May 2021
Learning in Deep Neural Networks Using a Biologically Inspired Optimizer Giorgia Dellaferrera Stanisław Woźniak Giacomo Indiveri A. Pantazi E. Eleftheriou 32 2 0 23 Apr 2021
Bidirectional Interaction between Visual and Motor Generative Models using Predictive Coding and Active Inference Louis Annabi Alexandre Pitti M. Quoy 16 10 0 19 Apr 2021
Meta-Learning Bidirectional Update Rules Mark Sandler Max Vladymyrov A. Zhmoginov Nolan Miller Andrew Jackson T. Madams Blaise Agüera y Arcas 27 15 0 10 Apr 2021
A Gradient Estimator for Time-Varying Electrical Networks with Non-Linear Dissipation Jack D. Kendall 14 6 0 09 Mar 2021
Reverse Differentiation via Predictive Coding Tommaso Salvatori Yuhang Song Thomas Lukasiewicz Rafal Bogacz Zhenghua Xu PINN 30 26 0 08 Mar 2021
Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-pruned Sign-symmetric Feedback Alignment Ziyang Hong C. Yue 29 2 0 04 Mar 2021
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks Sander Dalm Nasir Ahmad L. Ambrogioni Marcel van Gerven 36 1 0 23 Feb 2021
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training Yulin Wang Zanlin Ni Shiji Song Le Yang Gao Huang 25 83 0 26 Jan 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 69 13 0 06 Jan 2021
Training DNNs in O(1) memory with MEM-DFA using Random Matrices Tien Chu Kamil Mykitiuk Miron Szewczyk Adam Wiktor Z. Wojna 18 2 0 21 Dec 2020
The Neural Coding Framework for Learning Generative Models Alexander Ororbia Daniel Kifer GAN 26 65 0 07 Dec 2020
Align, then memorise: the dynamics of learning with feedback alignment Maria Refinetti Stéphane dÁscoli Ruben Ohana Sebastian Goldt 31 36 0 24 Nov 2020
A More Biologically Plausible Local Learning Rule for ANNs Shashi Kant Gupta AAML 17 2 0 24 Nov 2020
On-Chip Error-triggered Learning of Multi-layer Memristive Spiking Neural Networks Melika Payvand M. Fouda Fadi J. Kurdahi A. Eltawil Emre Neftci 35 29 0 21 Nov 2020
Identifying Learning Rules From Neural Network Observables Aran Nayebi S. Srivastava Surya Ganguli Daniel L. K. Yamins 19 21 0 22 Oct 2020
Local plasticity rules can learn deep representations using self-supervised contrastive predictions Bernd Illing Jean-Paul Ventura G. Bellec W. Gerstner SSL DRL 59 69 0 16 Oct 2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 22 0 0 13 Oct 2020
Deep Reservoir Networks with Learned Hidden Reservoir Weights using Direct Feedback Alignment Matthew Evanusa Cornelia Fermuller Yiannis Aloimonos AI4TS 13 1 0 13 Oct 2020
Differentially Private Deep Learning with Direct Feedback Alignment Jaewoo Lee Daniel Kifer FedML 25 9 0 08 Oct 2020
Relaxing the Constraints on Predictive Coding Models Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley 26 23 0 02 Oct 2020
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules R. Neven Marian Verhelst Tinne Tuytelaars Toon Goedemé 31 1 0 21 Sep 2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley ODL 28 16 0 11 Sep 2020
LoCo: Local Contrastive Representation Learning Yuwen Xiong Mengye Ren R. Urtasun SSL DRL 35 69 0 04 Aug 2020
Online Spatio-Temporal Learning in Deep Neural Networks Thomas Bohnstingl Stanislaw Wo'zniak Wolfgang Maass A. Pantazi E. Eleftheriou 29 43 0 24 Jul 2020
Biological credit assignment through dynamic inversion of feedforward networks William F. Podlaski C. Machens 27 19 0 10 Jul 2020
MPLP: Learning a Message Passing Learning Protocol E. Randazzo Eyvind Niklasson A. Mordvintsev 22 4 0 02 Jul 2020
A Theoretical Framework for Target Propagation Alexander Meulemans Francesco S. Carzaniga Johan A. K. Suykens João Sacramento Benjamin Grewe AAML 33 77 0 25 Jun 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures Julien Launay Iacopo Poli Franccois Boniface Florent Krzakala 41 63 0 23 Jun 2020
Extension of Direct Feedback Alignment to Convolutional and Recurrent Neural Network for Bio-plausible Deep Learning Donghyeon Han Gwangtae Park Junha Ryu H. Yoo 3DV 17 5 0 23 Jun 2020
Learning to Learn with Feedback and Local Plasticity Jack W Lindsey Ashok Litwin-Kumar CLL 34 32 0 16 Jun 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 24 34 0 12 Jun 2020
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks Julien Launay Iacopo Poli Kilian Muller I. Carron L. Daudet Florent Krzakala S. Gigan 11 6 0 02 Jun 2020
A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas Charlotte Frenkel J. Legat D. Bol 19 43 0 13 May 2020
Towards On-Chip Bayesian Neuromorphic Learning Nathan Wycoff Prasanna Balaprakash Fangfang Xia 19 1 0 05 May 2020
Why should we add early exits to neural networks? Simone Scardapane M. Scarpiniti E. Baccarelli A. Uncini 16 117 0 27 Apr 2020
Overcoming the Weight Transport Problem via Spike-Timing-Dependent Weight Inference Nasir Ahmad L. Ambrogioni Marcel van Gerven 23 2 0 09 Mar 2020
Two Routes to Scalable Credit Assignment without Weight Symmetry D. Kunin Aran Nayebi Javier Sagastuy-Breña Surya Ganguli Jonathan M. Bloom Daniel L. K. Yamins 34 32 0 28 Feb 2020
Contrastive Similarity Matching for Supervised Learning Shanshan Qin N. Mudur Cengiz Pehlevan SSL DRL 22 1 0 24 Feb 2020
Large-Scale Gradient-Free Deep Learning with Recursive Local Representation Alignment Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles 23 2 0 10 Feb 2020
Sideways: Depth-Parallel Training of Video Models Mateusz Malinowski G. Swirszcz João Carreira Viorica Patraucean MDE 49 13 0 17 Jan 2020
A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design Yusuke Sakemi K. Morino Takashi Morie Kazuyuki Aihara 8 32 0 08 Jan 2020
Are skip connections necessary for biologically plausible learning rules? Daniel Jiwoong Im Rutuja Patil K. Branson 14 1 0 04 Dec 2019
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks Thomas Mesnard Gaetan Vignoud João Sacramento Walter Senn Yoshua Bengio 27 7 0 15 Nov 2019
Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks D. Obeid Hugo Ramambason Cengiz Pehlevan FedML 14 20 0 11 Oct 2019
A Survey of Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization Alireza Ghods D. Cook 21 1 0 10 Sep 2019
On the Acceleration of Deep Learning Model Parallelism with Staleness An Xu Zhouyuan Huo Heng-Chiao Huang 16 37 0 05 Sep 2019
Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks Charlotte Frenkel M. Lefebvre D. Bol 16 23 0 03 Sep 2019