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NIPS
2007
13 years 9 months ago
Neural characterization in partially observed populations of spiking neurons
Point process encoding models provide powerful statistical methods for understanding the responses of neurons to sensory stimuli. Although these models have been successfully appl...
Jonathan Pillow, Peter E. Latham
JISE
2010
144views more  JISE 2010»
13 years 2 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
IJON
2006
90views more  IJON 2006»
13 years 7 months ago
Reinforcement learning of a simple control task using the spike response model
In this work, we propose a variation of a direct reinforcement learning algorithm, suitable for usage with spiking neurons based on the spike response model (SRM). The SRM is a bi...
Murilo Saraiva de Queiroz, Roberto Coelho de Berr&...
ESANN
2006
13 years 8 months ago
Saliency extraction with a distributed spiking neural network
We present a distributed spiking neuron network (SNN) for handling low-level visual perception in order to extract salient locations in robot camera images. We describe a new metho...
Sylvain Chevallier, Philippe Tarroux, Hél&e...
CVPR
2012
IEEE
11 years 10 months ago
The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle seg
The use of statistical pattern recognition models to segment the left ventricle of the heart in ultrasound images has gained substantial attention over the last few years. The mai...
Gustavo Carneiro, Jacinto C. Nascimento