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
Scaling Forward Gradient With Local Losses Mengye Ren Simon Kornblith Renjie Liao Geoffrey E. Hinton 81 49 0 07 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon Cengiz Pehlevan 41 22 0 05 Oct 2022
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits Lyes Khacef Philipp Klein M. Cartiglia Arianna Rubino Giacomo Indiveri Elisabetta Chicca 27 35 0 30 Sep 2022
Depth-Wise Attention (DWAtt): A Layer Fusion Method for Data-Efficient Classification Muhammad N. ElNokrashy Badr AlKhamissi Mona T. Diab MoMe 25 4 0 30 Sep 2022
Hebbian Deep Learning Without Feedback Adrien Journé Hector Garcia Rodriguez Qinghai Guo Timoleon Moraitis AAML 31 49 0 23 Sep 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations Axel Laborieux Friedemann Zenke 41 33 0 01 Sep 2022
Scalable Nanophotonic-Electronic Spiking Neural Networks Luis El Srouji Mehmet Yun-Jhu Lee Berkay On Li Zhang Fellow Ieee Fellow Optica S.J. Ben Yoo 26 6 0 28 Aug 2022
Learning with Local Gradients at the Edge M. Lomnitz Z. Daniels David C. Zhang M. Piacentino 34 1 0 17 Aug 2022
Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network Jian-Hui Chen Cheng-Lin Liu Zuoren Wang 28 0 0 01 Aug 2022
The least-control principle for local learning at equilibrium Alexander Meulemans Nicolas Zucchet Seijin Kobayashi J. Oswald João Sacramento 28 20 0 04 Jul 2022
Self-Supervised Pretraining for Differentially Private Learning Arash Asadian Evan Weidner Lei Jiang PICV 29 3 0 14 Jun 2022
A Robust Backpropagation-Free Framework for Images Timothy Zee Alexander Ororbia A. Mali Ifeoma Nwogu 28 1 0 03 Jun 2022
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning Beren Millidge Yuhang Song Tommaso Salvatori Thomas Lukasiewicz Rafal Bogacz 31 21 0 31 May 2022
A comparative study of back propagation and its alternatives on multilayer perceptrons John F. Waldo AAML 24 1 0 31 May 2022
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons Leon Lufkin Ashish Puri Ganlin Song Xinyi Zhong John D. Lafferty 21 1 0 26 May 2022
Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks Sunil Pai Zhanghao Sun Tyler W. Hughes Taewon Park Ben Bartlett ... F. Morichetti A. Melloni S. Fan O. Solgaard David A. B. Miller 20 178 0 17 May 2022
A Computational Framework of Cortical Microcircuits Approximates Sign-concordant Random Backpropagation Yukun Yang Peng Li 30 1 0 15 May 2022
Minimizing Control for Credit Assignment with Strong Feedback Alexander Meulemans Matilde Tristany Farinha Maria R. Cervera João Sacramento Benjamin Grewe 19 17 0 14 Apr 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses Robik Shrestha Kushal Kafle Christopher Kanan CML 35 13 0 05 Apr 2022
Signal Propagation: A Framework for Learning and Inference In a Forward Pass Adam A. Kohan E. Rietman H. Siegelmann 27 26 0 04 Apr 2022
Physical Deep Learning with Biologically Plausible Training Method M. Nakajima Katsuma Inoue Kenji Tanaka Yasuo Kuniyoshi Toshikazu Hashimoto Kohei Nakajima AI4CE 39 3 0 01 Apr 2022
Constrained Parameter Inference as a Principle for Learning Nasir Ahmad Ellen Schrader Marcel van Gerven 20 10 0 22 Mar 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets M. Ernoult Fabrice Normandin A. Moudgil Sean Spinney Eugene Belilovsky Irina Rish Blake A. Richards Yoshua Bengio 19 28 0 31 Jan 2022
Eigenvalues of Autoencoders in Training and at Initialization Ben Dees S. Agarwala Corey Lowman 24 0 0 27 Jan 2022
An Empirical Analysis of Recurrent Learning Algorithms In Neural Lossy Image Compression Systems A. Mali Alexander Ororbia Daniel Kifer L. Giles 19 4 0 27 Jan 2022
Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass Giorgia Dellaferrera Gabriel Kreiman 31 53 0 27 Jan 2022
PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++ Jae-Su Song Fangzhen Lin MQ 7 7 0 08 Jan 2022
Including STDP to eligibility propagation in multi-layer recurrent spiking neural networks Werner van der Veen 41 1 0 05 Jan 2022
Target Propagation via Regularized Inversion Vincent Roulet Zaïd Harchaoui BDL AAML 27 4 0 02 Dec 2021
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization Shivam Garg Santosh Vempala 33 3 0 17 Nov 2021
Silicon Photonic Architecture for Training Deep Neural Networks with Direct Feedback Alignment M. Filipovich Zhimu Guo M. Al-Qadasi Bicky A. Marquez Hugh Morison V. Sorger Paul R. Prucnal S. Shekhar B. Shastri 33 52 0 12 Nov 2021
Cooperative Deep $Q$ -learning Framework for Environments Providing Image Feedback Krishnan Raghavan Vignesh Narayanan S. Jagannathan VLM OffRL 26 1 0 28 Oct 2021
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization Jiaqi Gu Hanqing Zhu Chenghao Feng Zixuan Jiang Ray T. Chen David Z. Pan 26 29 0 27 Oct 2021
BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks Guangzhi Tang Neelesh Kumar Ioannis E. Polykretis Konstantinos Michmizos 26 6 0 27 Oct 2021
Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks M. Girotti Ioannis Mitliagkas Gauthier Gidel 24 1 0 20 Oct 2021
Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA Y. Kadokawa Yoshihisa Tsurumine Takamitsu Matsubara OffRL 37 4 0 10 Sep 2021
Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms Albert Jiménez Sanfiz Mohamed Akrout OOD AAML 22 8 0 30 Aug 2021
Tourbillon: a Physically Plausible Neural Architecture Mohammadamin Tavakoli Peter Sadowski Pierre Baldi 29 0 0 13 Jul 2021
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks Timoleon Moraitis Dmitry Toichkin Adrien Journé Yansong Chua Qinghai Guo AAML BDL 68 28 0 12 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 29 4 0 06 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 25 7 0 30 Jun 2021
Towards Biologically Plausible Convolutional Networks Roman Pogodin Yash Mehta Timothy Lillicrap P. Latham 28 22 0 22 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 44 9 0 15 Jun 2021
Gradient Forward-Propagation for Large-Scale Temporal Video Modelling Mateusz Malinowski Dimitrios Vytiniotis G. Swirszcz Viorica Patraucean João Carreira 30 8 0 15 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans Matilde Tristany Farinha Javier García Ordónez Pau Vilimelis Aceituno João Sacramento Benjamin Grewe 31 35 0 15 Jun 2021
Low-memory stochastic backpropagation with multi-channel randomized trace estimation M. Louboutin Ali Siahkoohi Rongrong Wang Felix J. Herrmann 21 0 0 13 Jun 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning Eugene Belilovsky Louis Leconte Lucas Caccia Michael Eickenberg Edouard Oyallon 24 7 0 11 Jun 2021
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights Ganlin Song Ruitu Xu John D. Lafferty ODL 59 21 0 10 Jun 2021
Credit Assignment Through Broadcasting a Global Error Vector David G. Clark L. F. Abbott SueYeon Chung 30 23 0 08 Jun 2021
Photonic Differential Privacy with Direct Feedback Alignment Ruben Ohana H. M. Ruiz Julien Launay Alessandro Cappelli Iacopo Poli L. Ralaivola A. Rakotomamonjy 27 8 0 07 Jun 2021