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» Input Modeling Using Quantile Statistical Methods
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NIPS
2007
15 years 4 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
181
Voted
TSMC
2008
225views more  TSMC 2008»
15 years 2 months ago
Robust Methods for Geometric Primitive Recovery and Estimation From Range Images
We present a method for the recovery of partially occluded 3D geometric primitives from range images which might also include non-primitive objects. The method uses a technique for...
Irina Lavva, Eyal Hameiri, Ilan Shimshoni
ECCV
2006
Springer
16 years 4 months ago
Uncalibrated Factorization Using a Variable Symmetric Affine Camera
Abstract. In order to reconstruct 3-D Euclidean shape by the TomasiKanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and par...
Ken-ichi Kanatani, Yasuyuki Sugaya, Hanno Ackerman...
ICA
2004
Springer
15 years 8 months ago
Non-linear ICA by Using Isometric Dimensionality Reduction
In usual ICA methods, sources are typically estimated by maximizing a measure of their statistical independence. This paper explains how to perform non-linear ICA by preprocessing ...
John Aldo Lee, Christian Jutten, Michel Verleysen
139
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ISNN
2005
Springer
15 years 8 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang