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» Estimating random variables from random sparse observations
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CORR
2010
Springer
129views Education» more  CORR 2010»
13 years 7 months ago
Estimation in Gaussian Noise: Properties of the Minimum Mean-Square Error
Consider the minimum mean-square error (MMSE) of estimating an arbitrary random variable from its observation contaminated by Gaussian noise. The MMSE can be regarded as a function...
Dongning Guo, Yihong Wu, Shlomo Shamai, Sergio Ver...
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 4 months ago
CUR from a Sparse Optimization Viewpoint
The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...
Jacob Bien, Ya Xu, Michael W. Mahoney
ICCD
2001
IEEE
119views Hardware» more  ICCD 2001»
14 years 4 months ago
A Functional Validation Technique: Biased-Random Simulation Guided by Observability-Based Coverage
We present a simulation-based semi-formal verification method for sequential circuits described at the registertransfer level. The method consists of an iterative loop where cove...
Serdar Tasiran, Farzan Fallah, David G. Chinnery, ...
NIPS
2004
13 years 8 months ago
Conditional Random Fields for Object Recognition
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects are modeled as flexible constellations of parts co...
Ariadna Quattoni, Michael Collins, Trevor Darrell
CVPR
2010
IEEE
13 years 10 months ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper