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» Using Learning for Approximation in Stochastic Processes
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IJON
2007
99views more  IJON 2007»
13 years 7 months ago
Criticality of avalanche dynamics in adaptive recurrent networks
In many studies of self-organized criticality (SOC), branching processes were used to model the dynamics of the activity of the system during avalanches. This mathematical simpliï...
Anna Levina, Udo Ernst, J. Michael Herrmann
PAMI
2008
250views more  PAMI 2008»
13 years 7 months ago
Combined Top-Down/Bottom-Up Segmentation
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Eran Borenstein, Shimon Ullman
ICIP
2006
IEEE
14 years 9 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
NIPS
2004
13 years 8 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson
BMCBI
2008
132views more  BMCBI 2008»
13 years 7 months ago
Clustering ionic flow blockade toggles with a Mixture of HMMs
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties with potential implications f...
Alexander G. Churbanov, Stephen Winters-Hilt