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ICDT
2009
ACM
129views Database» more  ICDT 2009»
16 years 1 months ago
Faster join-projects and sparse matrix multiplications
Computing an equi-join followed by a duplicate eliminating projection is conventionally done by performing the two operations in serial. If some join attribute is projected away t...
Rasmus Resen Amossen, Rasmus Pagh
107
Voted
ICA
2007
Springer
15 years 4 months ago
Estimating the Mixing Matrix in Sparse Component Analysis Based on Converting a Multiple Dominant to a Single Dominant Problem
We propose a new method for estimating the mixing matrix, A, in the linear model x(t) = As(t), t = 1, . . . , T, for the problem of underdetermined Sparse Component Analysis (SCA)....
Nima Noorshams, Massoud Babaie-Zadeh, Christian Ju...
122
Voted
UAI
2008
15 years 2 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
MFCS
2010
Springer
14 years 11 months ago
Evaluating Non-square Sparse Bilinear Forms on Multiple Vector Pairs in the I/O-Model
We consider evaluating one bilinear form defined by a sparse Ny × Nx matrix A having h entries on w pairs of vectors The model of computation is the semiring I/O-model with main ...
Gero Greiner, Riko Jacob
94
Voted
CORR
2011
Springer
200views Education» more  CORR 2011»
14 years 7 months ago
Sequential Analysis in High Dimensional Multiple Testing and Sparse Recovery
—This paper studies the problem of high-dimensional multiple testing and sparse recovery from the perspective of sequential analysis. In this setting, the probability of error is...
Matt Malloy, Robert Nowak