Supervised learning with decision margins in pools of spiking neurons

DOI10.1007/s10827-014-0505-9zbMath1409.92047OpenAlexW2026758814WikidataQ34157379 ScholiaQ34157379MaRDI QIDQ1732642

Kenneth D. Harris, Charlotte Le Mouel, Pierre Yger

Publication date: 25 March 2019

Published in: Journal of Computational Neuroscience (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10827-014-0505-9

zbMATH Keywords

supervised learningspiking neuronssupport vector machinekeywordstempotron

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural biology (92C20)

Uses Software

• Scikit
• Pynn
• NEST

Cites Work

• Unnamed Item
• Unnamed Item
• Error-backpropagation in temporally encoded networks of spiking neurons
• Support-vector networks
• The interaction space of neural networks with sign-constrained synapses
• On the Classification Capability of Sign-Constrained Perceptrons
• Reinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity
• Competitive STDP-Based Spike Pattern Learning
• Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting
• A New Supervised Learning Algorithm for Spiking Neurons
• The space of interactions in neural network models
• Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning
• What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?

This page was built for publication: Supervised learning with decision margins in pools of spiking neurons