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JORS
2011
67views more  JORS 2011»
15 years 1 months ago
Robust parameter design optimization of simulation experiments using stochastic perturbation methods
Stochastic perturbation methods can be applied to problems for which either the objective function is represented analytically, or the objective function is the result of a simula...
A. K. Miranda, E. Del Castillo
ICASSP
2011
IEEE
14 years 10 months ago
Gaussian mixture modeling for source localization
Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density fun...
John T. Flåm, Joakim Jalden, Saikat Chatterj...
173
Voted
SODA
2010
ACM
164views Algorithms» more  SODA 2010»
16 years 3 months ago
Differentially Private Approximation Algorithms
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
PLDI
2011
ACM
14 years 9 months ago
EnerJ: approximate data types for safe and general low-power computation
Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Re...
Adrian Sampson, Werner Dietl, Emily Fortuna, Danus...
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 6 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...