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WSNA
2003
ACM
13 years 12 months ago
Parametric probabilistic sensor network routing
Motivated by realistic sensor network scenarios that have mis-informed nodes and variable network topologies, we propose a fundamentally different approach to routing that combine...
Christopher L. Barrett, Stephan Eidenbenz, Lukas K...
NAS
2010
IEEE
13 years 4 months ago
A Probabilistic Routing Protocol for Heterogeneous Sensor Networks
The past five years witnessed a rapid development in wireless sensor networks, which have been widely used in military and civilian applications. Due to different requirements in t...
Yuefei Hu, Wenzhong Li, Xiao Chen, Xin Chen, Sangl...
ICANN
2007
Springer
14 years 26 days ago
Structure Learning with Nonparametric Decomposable Models
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Anton Schwaighofer, Mathäus Dejori, Volker Tr...
IJON
2010
109views more  IJON 2010»
13 years 1 months ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney
WD
2010
13 years 4 months ago
Enhancing FEC application in LTE cellular networks
3rd Generation Partnership Project's (3GPP) Long Term Evolution (LTE) is focused on enhancing the Universal Terrestrial Radio Access (UTRA). Evolved-Multimedia Broadcast and M...
Antonios G. Alexiou, Christos Bouras, Vasileios Ko...