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» A Practical Method for the Sparse Resultant
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ROBOCUP
2005
Springer
164views Robotics» more  ROBOCUP 2005»
15 years 3 months ago
Laser-Based Localization with Sparse Landmarks
Abstract. Self-localization in dynamic environments is a central problem in mobile robotics and is well studied in the literature. One of the most popular methods is the Monte Carl...
Andreas Strack, Alexander Ferrein, Gerhard Lakemey...
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
14 years 7 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
ACIVS
2005
Springer
15 years 3 months ago
Image De-Quantizing via Enforcing Sparseness in Overcomplete Representations
We describe a method for removing quantization artifacts (de-quantizing) in the image domain, by enforcing a high degree of sparseness in its representation with an overcomplete or...
Luis Mancera, Javier Portilla
AMC
2005
87views more  AMC 2005»
14 years 9 months ago
Wavelet based preconditioners for sparse linear systems
A class of efficient preconditioners based on Daubechies family of wavelets for sparse, unsymmetric linear systems that arise in numerical solution of Partial Differential Equatio...
B. V. Rathish Kumar, Mani Mehra
ICASSP
2008
IEEE
15 years 4 months ago
Application of sparse signal recovery to pilot-assisted channel estimation
We examine the application of current research in sparse signal recovery to the problem of channel estimation. Specifically, using an Orthogonal Frequency Division Multiplexed (O...
Matthew Sharp, Anna Scaglione