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» Approximate Learning of Dynamic Models
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ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
15 years 8 months ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
CVPR
2010
IEEE
13 years 11 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
134
Voted
TSMC
2008
177views more  TSMC 2008»
15 years 8 days ago
Adaptive Critic Learning Techniques for Engine Torque and Air-Fuel Ratio Control
A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning con...
Derong Liu, Hossein Javaherian, Olesia Kovalenko, ...
ICML
2010
IEEE
14 years 11 months ago
Approximate Predictive Representations of Partially Observable Systems
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Monica Dinculescu, Doina Precup
NIPS
1994
15 years 3 months ago
Generalization in Reinforcement Learning: Safely Approximating the Value Function
To appear in: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., Advances in Neural Information Processing Systems 7, MIT Press, Cambridge MA, 1995. A straightforward approach to t...
Justin A. Boyan, Andrew W. Moore