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» A Simple Model of Long-Term Spike Train Regularization
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NECO
2007
258views more  NECO 2007»
13 years 7 months ago
Reinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity
The persistent modification of synaptic efficacy as a function of the relative timing of pre- and postsynaptic spikes is a phenomenon known as spiketiming-dependent plasticity (...
Razvan V. Florian
NIPS
1994
13 years 8 months ago
From Data Distributions to Regularization in Invariant Learning
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Todd K. Leen
NIPS
1998
13 years 8 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
JCNS
2006
59views more  JCNS 2006»
13 years 7 months ago
Spatio-temporal filtering properties of a dendritic cable with active spines: A modeling study in the spike-diffuse-spike framew
The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whils...
Yulia Timofeeva, Gabriel J. Lord, Stephen Coombes
PRL
2010
188views more  PRL 2010»
13 years 5 months ago
Sparsity preserving discriminant analysis for single training image face recognition
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Lishan Qiao, Songcan Chen, Xiaoyang Tan