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» A Practical Method for the Sparse Resultant
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CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 5 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
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
13 years 6 months ago
Sparse Unsupervised Dimensionality Reduction Algorithms
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
Wenjun Dou, Guang Dai, Congfu Xu, Zhihua Zhang
VTC
2008
IEEE
105views Communications» more  VTC 2008»
14 years 2 months ago
Practical Results of High Resolution AOA Estimation by the Synthetic Array
— In this paper, a new method for AOA estimation, based on the synthetic ESPRIT algorithm is described and tested with actual CDMA signals. Physical size constraints of handheld ...
Ali Broumandan, John Nielsen, Gérard Lachap...
ICASSP
2011
IEEE
12 years 11 months ago
Revisiting adaptive least-squares estimation and application to online sparse signal recovery
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
Konstantinos Slavakis, Yannis Kopsinis, Sergios Th...
SODA
2012
ACM
209views Algorithms» more  SODA 2012»
11 years 10 months ago
Simple and practical algorithm for sparse Fourier transform
We consider the sparse Fourier transform problem: given a complex vector x of length n, and a parameter k, estimate the k largest (in magnitude) coefficients of the Fourier transf...
Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric ...