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167
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JMLR
2010
148views more  JMLR 2010»
14 years 8 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
139
Voted
JMLR
2012
13 years 4 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
117
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ICASSP
2010
IEEE
15 years 11 days ago
A hierarchical Bayesian model for frame representation
In many signal processing problems, it may be fruitful to represent the signal under study in a redundant linear decomposition called a frame. If a probabilistic approach is adopt...
Lotfi Chaâri, Jean-Christophe Pesquet, Jean-...
JDCTA
2010
126views more  JDCTA 2010»
14 years 8 months ago
Continuous Neural Decoding Method Based on General Regression Neural Network
Neural decoding is an important task for understanding how the biological nervous system performs computation and communication. This paper introduces a novel continuous neural de...
Jianhua Dai, Xiaochun Liu, Shaomin Zhang, Huaijian...
112
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TCAD
1998
127views more  TCAD 1998»
15 years 1 months ago
Gate-level power estimation using tagged probabilistic simulation
In this paper, we present a probabilistic simulation technique to estimate the power consumption of a cmos circuit under a general delay model. This technique is based on the noti...
Chih-Shun Ding, Chi-Ying Tsui, Massoud Pedram