Enforcing balance allows local supervised learning in spiking recurrent networks.
Ralph BourdoukanSophie DenèvePublished in: NIPS (2015)
Keyphrases
- recurrent networks
- feed forward
- supervised learning
- recurrent neural networks
- biologically inspired
- back propagation
- biologically plausible
- neural network
- neuron model
- hebbian learning
- unsupervised learning
- spiking neural networks
- artificial neural networks
- learning algorithm
- training data
- learning problems
- supervised classification
- training examples
- visual cortex
- semi supervised
- unlabeled data
- semi supervised learning
- bio inspired
- spiking neurons
- reinforcement learning
- active learning
- multiple instance learning
- statistical learning
- artificial intelligence
- learning tasks
- labeled data
- learning rules
- training set
- machine learning
- basal ganglia
- feed forward neural networks
- supervised machine learning
- neural models
- data sets
- training samples
- multi modal
- high dimensional