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ICASSP
2010
IEEE
15 years 2 months ago
An adaptive level of detail approach to nonlinear estimation
In this work, we present a general method for approximating nonlinear transformations of Gaussian mixture random variables. It is based on transforming the individual Gaussians wi...
Friedrich Faubel, Dietrich Klakow
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 4 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
BMCBI
2011
14 years 6 months ago
ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
Background: With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies hav...
Osvaldo Zagordi, Arnab Bhattacharya, Nicholas Erik...
ISLPED
2007
ACM
109views Hardware» more  ISLPED 2007»
15 years 3 months ago
A multi-model power estimation engine for accuracy optimization
RTL power macromodeling is a mature research topic with a variety of equation and table-based approaches. Despite its maturity, macromodeling is not yet widely accepted as an indu...
Felipe Klein, Guido Araujo, Rodolfo Azevedo, Rober...
89
Voted
ADCM
2010
59views more  ADCM 2010»
15 years 2 months ago
Sampling inequalities for infinitely smooth functions, with applications to interpolation and machine learning
Sampling inequalities give a precise formulation of the fact that a differentiable function cannot attain large values, if its derivatives are bounded and if it is small on a suff...
Christian Rieger, Barbara Zwicknagl