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» A Fast Random Sampling Algorithm for Sparsifying Matrices
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STOC
2012
ACM
192views Algorithms» more  STOC 2012»
11 years 10 months ago
Nearly optimal sparse fourier transform
We consider the problem of computing the k-sparse approximation to the discrete Fourier transform of an ndimensional signal. We show: • An O(k log n)-time randomized algorithm f...
Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric ...
WSC
2007
13 years 10 months ago
Analysis and generation of random vectors with copulas
Copulas are used in finance and insurance for modeling stochastic dependency. They comprehend the entire dependence structure, not only the correlations. Here they are estimated ...
Johann Christoph Strelen, Feras Nassaj
NIPS
2004
13 years 9 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson
SODA
2010
ACM
169views Algorithms» more  SODA 2010»
14 years 5 months ago
Efficiently Decodable Non-adaptive Group Testing
We consider the following "efficiently decodable" nonadaptive group testing problem. There is an unknown string x {0, 1}n with at most d ones in it. We are allowed to t...
Piotr Indyk, Hung Q. Ngo, Atri Rudra
DKE
2006
67views more  DKE 2006»
13 years 7 months ago
Indexed-based density biased sampling for clustering applications
Density biased sampling (DBS) has been proposed to address the limitations of Uniform sampling, by producing the desired probability distribution in the sample. The ease of produc...
Alexandros Nanopoulos, Yannis Theodoridis, Yannis ...