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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...
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 ...
CVPR
2010
IEEE
12 years 4 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
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