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ICASSP
2011
IEEE
12 years 10 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
STACS
2007
Springer
14 years 21 days ago
New Approximation Algorithms for Minimum Cycle Bases of Graphs
We consider the problem of computing an approximate minimum cycle basis of an undirected non-negative edge-weighted graph G with m edges and n vertices; the extension to directed ...
Telikepalli Kavitha, Kurt Mehlhorn, Dimitrios Mich...
JMLR
2011
148views more  JMLR 2011»
13 years 1 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
SIAMMAX
2010
224views more  SIAMMAX 2010»
13 years 1 months ago
Robust Approximate Cholesky Factorization of Rank-Structured Symmetric Positive Definite Matrices
Abstract. Given a symmetric positive definite matrix A, we compute a structured approximate Cholesky factorization A RT R up to any desired accuracy, where R is an upper triangula...
Jianlin Xia, Ming Gu
DC
2010
13 years 6 months ago
Distributed algorithms for ultrasparse spanners and linear size skeletons
We present efficient algorithms for computing very sparse low distortion spanners in distributed networks and prove some non-trivial lower bounds on the tradeoff between time, spar...
Seth Pettie