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SIAMJO
2002
14 years 11 months ago
2002
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
ICML
2009
IEEE
16 years 19 days ago
2009
IEEE
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
ICASSP
2008
IEEE
15 years 6 months ago
2008
IEEE
We attempt to quantify the possible gains that can be achieved by examining a rate-distortion competition between a conventional and a compressive sampling solution to data rate r...
IPMU
2010
Springer
14 years 10 months ago
2010
Springer
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
MTA
2010
14 years 10 months ago
2010
Abstract In this paper we propose a reduced-reference quality assessment algorithm which computes an approximation of the Structural SIMilarity (SSIM) metrics exploiting coding too...