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» Hardware-Efficient Belief Propagation
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IROS
2007
IEEE
159views Robotics» more  IROS 2007»
15 years 6 months ago
Approximate covariance estimation in graphical approaches to SLAM
— Smoothing and optimization approaches are an effective means for solving the simultaneous localization and mapping (SLAM) problem. Most of the existing techniques focus mainly ...
Gian Diego Tipaldi, Giorgio Grisetti, Wolfram Burg...
NIPS
2008
15 years 1 months ago
Bounds on marginal probability distributions
We propose a novel bound on single-variable marginal probability distributions in factor graphs with discrete variables. The bound is obtained by propagating local bounds (convex ...
Joris M. Mooij, Hilbert J. Kappen
CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 7 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
NIPS
2003
15 years 1 months ago
Laplace Propagation
We present a novel method for approximate inference in Bayesian models and regularized risk functionals. It is based on the propagation of mean and variance derived from the Lapla...
Alexander J. Smola, Vishy Vishwanathan, Eleazar Es...
CDC
2009
IEEE
158views Control Systems» more  CDC 2009»
15 years 3 months ago
Multiple target detection using Bayesian learning
In this paper, we study multiple target detection using Bayesian learning. The main aim of the paper is to present a computationally efficient way to compute the belief map update ...
Sujit Nair, Konda Reddy Chevva, Houman Owhadi, Jer...