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LSSC
2001
Springer
14 years 1 months ago
A Quasi-Monte Carlo Method for Integration with Improved Convergence
Abstract. Quasi-Monte Carlo methods are based on the idea that random Monte Carlo techniques can often be improved by replacing the underlying source of random numbers with a more ...
Aneta Karaivanova, Ivan Dimov, Sofiya Ivanovska
ATAL
2010
Springer
13 years 9 months ago
Divide-and-coordinate: DCOPs by agreement
In this paper we investigate an approach to provide approximate, anytime algorithms for DCOPs that can provide quality guarantees. At this aim, we propose the divide-and-coordinat...
Meritxell Vinyals, Marc Pujol, Juan A. Rodrí...
AUTOMATICA
2008
139views more  AUTOMATICA 2008»
13 years 8 months ago
Structured low-rank approximation and its applications
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equival...
Ivan Markovsky
CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 3 months ago
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
CORR
2012
Springer
249views Education» more  CORR 2012»
12 years 4 months ago
Computing Cartograms with Optimal Complexity
We show how to compute cartograms with worst-case optimal polygonal complexity. Specifically we study rectilinear duals which are side-contact representations of a planar graph G ...
Md. Jawaherul Alam, Therese C. Biedl, Stefan Felsn...