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SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 9 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
AAAI
2008
13 years 10 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...
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 27 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