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» Detection of Stochastic Processes
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ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
14 years 4 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...
CDC
2009
IEEE
160views Control Systems» more  CDC 2009»
14 years 2 months ago
Control of impulsive renewal systems: Application to direct design in networked control
— We consider the control of impulsive systems with jumps triggered by a renewal process, that is, the intervals between jumps are independent and identically distributed. The co...
Duarte Antunes, João Pedro Hespanha, Carlos...
3DPVT
2006
IEEE
188views Visualization» more  3DPVT 2006»
14 years 1 months ago
Statistical Inference of Biological Structure and Point Spread Functions in 3D Microscopy
We present a novel method for detecting and quantifying 3D structure in stacks of microscopic images captured at incremental focal lengths. We express the image data as stochastic...
Joseph Schlecht, Kobus Barnard, Barry Pryor
NIPS
2001
13 years 11 months ago
An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures
This paper describes a clustering algorithm for vector quantizers using a "stochastic association model". It offers a new simple and powerful softmax adaptation rule. Th...
Takashi Morie, Tomohiro Matsuura, Makoto Nagata, A...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 4 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson