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STOC
2006
ACM
244views Algorithms» more  STOC 2006»
15 years 10 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle
ICASSP
2011
IEEE
14 years 1 months ago
Learning sparse dictionaries with a popularity-based model
Sparse signal representation based on overcomplete dictionaries has recently been extensively investigated, rendering the state-of-the-art results in signal, image and video proce...
Jianzhou Feng, Li Song, Xiaoming Huo, Xiaokang Yan...
ICASSP
2008
IEEE
15 years 4 months ago
Average case analysis of sparse recovery with thresholding : New bounds based on average dictionary coherence
This paper analyzes the performance of the simple thresholding algorithm for sparse signal representations. In particular, in order to be more realistic we introduce a new probabi...
Mohammad Golbabaee, Pierre Vandergheynst
SODA
2012
ACM
170views Algorithms» more  SODA 2012»
13 years 14 days ago
Compression via matroids: a randomized polynomial kernel for odd cycle transversal
The Odd Cycle Transversal problem (OCT) asks whether a given graph can be made bipartite by deleting at most k of its vertices. In a breakthrough result Reed, Smith, and Vetta (Op...
Stefan Kratsch, Magnus Wahlström
TSP
2010
14 years 4 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic