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» Algorithmic models for sensor networks
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NIPS
1997
15 years 8 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
IPPS
2006
IEEE
16 years 28 days ago
Analytical performance modelling of partially adaptive routing in wormhole hypercubes
Although several analytical models have been proposed in the literature for different interconnection networks with different routing algorithms, there is only one work dealing wi...
Ahmad Patooghy, Hamid Sarbazi-Azad
ICDCIT
2007
Springer
16 years 1 months ago
Self-stabilizing Routing Algorithms for Wireless Ad-Hoc Networks
This paper considers the problem of unicasting in wireless ad hoc networks. Unicasting is the problem of finding a route between a source and a destination and forwarding the mess...
Rohit Ashok Khot, Ravikant Poola, Kishore Kothapal...
TSP
2008
101views more  TSP 2008»
15 years 6 months ago
Optimal Node Density for Detection in Energy-Constrained Random Networks
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
Animashree Anandkumar, Lang Tong, Ananthram Swami
IS
2007
15 years 6 months ago
Evaluation of probabilistic queries over imprecise data in constantly-evolving environments
Sensors are often employed to monitor continuously changing entities like locations of moving objects and temperature. The sensor readings are reported to a database system, and a...
Reynold Cheng, Dmitri V. Kalashnikov, Sunil Prabha...