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» Approximating Component Selection
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ICTAI
2010
IEEE
15 years 21 days ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
119
Voted
CORR
2011
Springer
160views Education» more  CORR 2011»
14 years 7 months ago
Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences
The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mecha...
Jeroen Keppens, Qiang Shen
140
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CVPR
2012
IEEE
13 years 5 months ago
Hierarchical face parsing via deep learning
This paper investigates how to parse (segment) facial components from face images which may be partially occluded. We propose a novel face parser, which recasts segmentation of fa...
Ping Luo, Xiaogang Wang, Xiaoou Tang
IPMI
2001
Springer
16 years 4 months ago
Estimability of Spatio-temporal Activation in fMRI
Event-related functional magnetic resonance imaging (fMRI) is considered as an estimation and reconstruction problem. A linear model of the fMRI system based on the Fourier sampler...
Andre Lehovich, Harrison H. Barrett, Eric Clarkson...
111
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SSS
2009
Springer
15 years 10 months ago
Stability of Distributed Algorithms in the Face of Incessant Faults
Abstract. For large distributed systems built from inexpensive components, one expects to see incessant failures. This paper proposes two models for such faults and analyzes two we...
Robert E. Lee DeVille, Sayan Mitra