11 search results - page 2 / 3 » Bayesian Inference for Spiking Neuron Models with a Sparsity... |
ICDM
2009
IEEE
14 years 2 months ago
2009
IEEE
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
SIAMIS
2011
13 years 2 months ago
2011
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
NECO
2000
13 years 7 months ago
2000
Recent advances in the technology of multi-unit recordings make it possible to test Hebb's hypothesis that neurons do not function in isolation but are organized in assemblie...