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JMLR
2010
157views more  JMLR 2010»
13 years 18 days ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
ICIP
2007
IEEE
14 years 7 months ago
Color Image Denoising via Sparse 3D Collaborative Filtering with Grouping Constraint in Luminance-Chrominance Space
We propose an effective color image denoising method that exploits ltering in highly sparse local 3D transform domain in each channel of a luminance-chrominance color space. For e...
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik...
ISRR
2005
Springer
118views Robotics» more  ISRR 2005»
13 years 11 months ago
A Provably Consistent Method for Imposing Sparsity in Feature-Based SLAM Information Filters
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...
Matthew Walter, Ryan Eustice, John J. Leonard
CORR
2010
Springer
174views Education» more  CORR 2010»
13 years 5 months ago
Collaborative Spectrum Sensing from Sparse Observations in Cognitive Radio Networks
Spectrum sensing, which aims at detecting spectrum holes, is the precondition for the implementation of cognitive radio. Collaborative spectrum sensing among the cognitive radio n...
Jia Meng, Wotao Yin, Husheng Li, Ekram Hossain, Zh...
APLAS
2009
ACM
14 years 10 days ago
Scalable Context-Sensitive Points-to Analysis Using Multi-dimensional Bloom Filters
Abstract. Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the a...
Rupesh Nasre, Kaushik Rajan, Ramaswamy Govindaraja...