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TSP
2010
13 years 29 days ago
Covariance estimation in decomposable Gaussian graphical models
Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
Ami Wiesel, Yonina C. Eldar, Alfred O. Hero
COLT
2010
Springer
13 years 3 months ago
Nonparametric Bandits with Covariates
We consider a bandit problem which involves sequential sampling from two populations (arms). Each arm produces a noisy reward realization which depends on an observable random cov...
Philippe Rigollet, Assaf Zeevi
SIAMSC
2011
219views more  SIAMSC 2011»
13 years 1 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
TSP
2010
13 years 29 days ago
Shrinkage algorithms for MMSE covariance estimation
We address covariance estimation in the sense of minimum mean-squared error (MMSE) when the samples are Gaussian distributed. Specifically, we consider shrinkage methods which are ...
Yilun Chen, Ami Wiesel, Yonina C. Eldar, Alfred O....
VLDB
2007
ACM
118views Database» more  VLDB 2007»
14 years 6 months ago
Eliminating Impedance Mismatch in C++
Recently, the C# and the VISUAL BASIC communities were tantalized by the advent of LINQ [18]--the Language INtegrated Query technology from Microsoft. LINQ represents a set of lan...
Joseph Gil, Keren Lenz