Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
出版年份 2021 全文链接
标题
Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
作者
关键词
-
出版物
Frontiers in Neuroscience
Volume 15, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2021-02-11
DOI
10.3389/fnins.2021.629892
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Synaptic Plasticity Forms and Functions
- (2020) Jeffrey C. Magee et al. Annual Review of Neuroscience
- Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE)
- (2020) Jacques Kaiser et al. Frontiers in Neuroscience
- Low-Power Neuromorphic Hardware for Signal Processing Applications: A Review of Architectural and System-Level Design Approaches
- (2019) Bipin Rajendran et al. IEEE SIGNAL PROCESSING MAGAZINE
- MorphIC: A 65-nm 738k-Synapse/mm$^2$ Quad-Core Binary-Weight Digital Neuromorphic Processor With Stochastic Spike-Driven Online Learning
- (2019) Charlotte Frenkel et al. IEEE Transactions on Biomedical Circuits and Systems
- A 65-nm Neuromorphic Image Classification Processor With Energy-Efficient Training Through Direct Spike-Only Feedback
- (2019) Jeongwoo Park et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- Learning in the machine: Random backpropagation and the deep learning channel
- (2018) Pierre Baldi et al. ARTIFICIAL INTELLIGENCE
- Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
- (2018) Georgios Detorakis et al. Frontiers in Neuroscience
- Deep Supervised Learning Using Local Errors
- (2018) Hesham Mostafa et al. Frontiers in Neuroscience
- Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain
- (2018) Chetan Singh Thakur et al. Frontiers in Neuroscience
- Towards deep learning with segregated dendrites
- (2017) Jordan Guerguiev et al. eLife
- Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
- (2017) Emre O. Neftci et al. Frontiers in Neuroscience
- Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System
- (2017) Moritz B. Milde et al. Frontiers in Neurorobotics
- Random synaptic feedback weights support error backpropagation for deep learning
- (2016) Timothy P. Lillicrap et al. Nature Communications
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks
- (2015) Friedemann Zenke et al. Nature Communications
- Learning by the Dendritic Prediction of Somatic Spiking
- (2014) Robert Urbanczik et al. NEURON
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now