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» Entropy-based Adaptive Sampling
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AAAI
2008
13 years 9 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
TOG
2010
134views more  TOG 2010»
13 years 2 months ago
Unbiased, adaptive stochastic sampling for rendering inhomogeneous participating media
Realistic rendering of participating media is one of the major subjects in computer graphics. Monte Carlo techniques are widely used for realistic rendering because they provide u...
Yonghao Yue, Kei Iwasaki, Bing-Yu Chen, Yoshinori ...
PODS
2004
ACM
207views Database» more  PODS 2004»
14 years 7 months ago
Adaptive Sampling for Geometric Problems over Data Streams
Geometric coordinates are an integral part of many data streams. Examples include sensor locations in environmental monitoring, vehicle locations in traffic monitoring or battlefi...
John Hershberger, Subhash Suri
ICRA
2007
IEEE
160views Robotics» more  ICRA 2007»
14 years 1 months ago
Adaptive Sampling for Multi-Robot Wide-Area Exploration
— The exploration problem is a central issue in mobile robotics. A complete coverage is not practical if the environment is large with a few small hotspots, and the sampling cost...
Kian Hsiang Low, Geoffrey J. Gordon, John M. Dolan...
IPSN
2004
Springer
14 years 25 days ago
Backcasting: adaptive sampling for sensor networks
Wireless sensor networks provide an attractive approach to spatially monitoring environments. Wireless technology makes these systems relatively flexible, but also places heavy d...
Rebecca Willett, Aline Martin, Robert Nowak