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ISBI
2006
IEEE
16 years 19 days ago
Improve brain registration using machine learning methods
A machine learning method is introduced here to improve the accuracy of brain registration. Generally, different brain regions might need different types or sets of features for r...
Guorong Wu, Feihu Qi, Dinggang Shen
ICRA
2005
IEEE
159views Robotics» more  ICRA 2005»
16 years 6 days ago
Learning Sensory Feedback to CPG with Policy Gradient for Biped Locomotion
— This paper proposes a learning framework for a CPG-based biped locomotion controller using a policy gradient method. Our goal in this study is to develop an efficient learning...
Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, ...
NIPS
1996
15 years 8 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
ICML
2010
IEEE
15 years 7 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov
AAMAS
2007
Springer
15 years 6 months ago
Parallel Reinforcement Learning with Linear Function Approximation
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Matthew Grounds, Daniel Kudenko