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» Resampling methods for input modeling
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141
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AROBOTS
1999
104views more  AROBOTS 1999»
15 years 2 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
140
Voted
ECCV
2004
Springer
16 years 4 months ago
Automatic Non-rigid 3D Modeling from Video
We present a robust framework for estimating non-rigid 3D shape and motion in video sequences. Given an input video sequence, and a user-specified region to reconstruct, the algori...
Lorenzo Torresani, Aaron Hertzmann
91
Voted
WSC
1998
15 years 3 months ago
Integrating Neural Networks with Special Purpose Simulation
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Dany Hajjar, Simaan M. AbouRizk, Kevin Mather
IJDMB
2007
119views more  IJDMB 2007»
15 years 2 months ago
Simulation study in Probabilistic Boolean Network models for genetic regulatory networks
: Probabilistic Boolean Network (PBN) is widely used to model genetic regulatory networks. Evolution of the PBN is according to the transition probability matrix. Steady-state (lon...
Shuqin Zhang, Wai-Ki Ching, Michael K. Ng, Tatsuya...
IJON
2006
109views more  IJON 2006»
15 years 2 months ago
Integrating the improved CBP model with kernel SOM
In this paper, we first design a more generalized network model, Improved CBP, based on the same structure as Circular BackPropagation (CBP) proposed by Ridella et al. The novelty ...
Qun Dai, Songcan Chen