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NECO
2010
103views more  NECO 2010»
13 years 7 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
WSNA
2003
ACM
14 years 2 months ago
Asymptotically optimal time synchronization in dense sensor networks
We consider the problem of synchronization of all clocks in a sensor network, in the regime of asymptotically high node densities. We formulate this problem as one in which all cl...
An-Swol Hu, Sergio D. Servetto
CVPR
2012
IEEE
11 years 11 months ago
City scale geo-spatial trajectory estimation of a moving camera
This paper presents a novel method for estimating the geospatial trajectory of a moving camera with unknown intrinsic parameters, in a city-scale urban environment. The proposed m...
Gonzalo Vaca-Castano, Amir Roshan Zamir, Mubarak S...
DAGSTUHL
2007
13 years 10 months ago
On the Cost of Shifting Event Processing within Wireless Environments
With the emergence of wireless sensor networks, the issues of event recognition and processing have been partially shifted into the embedded domain. New processing capabilities on...
Kirsten Terfloth, Katharina Hahn, Agnès Voi...
ICASSP
2009
IEEE
14 years 3 months ago
Time-varying Opportunistic Protocol for maximizing sensor networks lifetime
We consider transmission scheduling by medium access control (MAC) protocols for energy limited wireless sensor networks (WSN) in order to maximize the network lifetime. Time-vary...
Kobi Cohen, Amir Leshem