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» Approximate algorithms for neural-Bayesian approaches
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ICML
2010
IEEE
14 years 11 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
ICML
2010
IEEE
14 years 11 months ago
Interactive Submodular Set Cover
We introduce a natural generalization of submodular set cover and exact active learning with a finite hypothesis class (query learning). We call this new problem interactive submo...
Andrew Guillory, Jeff Bilmes
GI
2009
Springer
14 years 7 months ago
Gaussian Mixture (GM) Passive Localization using Time Difference of Arrival (TDOA)
: This paper describes the passive emitter localization using Time Difference of Arrival (TDOA) measurements. It investigates various methods for estimating the solution of this no...
Regina Kaune
UAI
2004
14 years 11 months ago
On the Choice of Regions for Generalized Belief Propagation
Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...
Max Welling
MOBIHOC
2005
ACM
15 years 9 months ago
On the node-scheduling approach to topology control in ad hoc networks
: In this paper, we analyze the node scheduling approach of topology control in the context of reliable packet delivery. In node scheduling, only a minimum set of nodes needed for ...
Budhaditya Deb, Badri Nath