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» Estimating random variables from random sparse observations
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ASPDAC
2009
ACM
164views Hardware» more  ASPDAC 2009»
14 years 2 months ago
Accounting for non-linear dependence using function driven component analysis
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Lerong Cheng, Puneet Gupta, Lei He
AIME
2007
Springer
14 years 1 months ago
Variable Selection for Optimal Decision Making
This paper discusses variable selection for medical decision making; in particular decisions regarding when to provide treatment and which treatment to provide. Current variable se...
Lacey Gunter, Ji Zhu, Susan Murphy
INFOCOM
2011
IEEE
12 years 11 months ago
Modeling residual-geometric flow sampling
Abstract—Traffic monitoring and estimation of flow parameters in high speed routers have recently become challenging as the Internet grew in both scale and complexity. In this ...
Xiaoming Wang, Xiaoyong Li, Dmitri Loguinov
ICASSP
2010
IEEE
13 years 5 months ago
A sparse component model of source signals and its application to blind source separation
In this paper, we propose a new method of blind source separation (BSS) for music signals. Our method has the following characteristics: 1) the method is a combination of the spar...
Yu Kitano, Hirokazu Kameoka, Yosuke Izumi, Nobutak...
ICML
2004
IEEE
14 years 8 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh