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JMLR
2010
103views more  JMLR 2010»
13 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ICML
2008
IEEE
14 years 7 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
TMI
2002
107views more  TMI 2002»
13 years 6 months ago
Volumetric Segmentation of Brain Images Using Parallel Genetic Algorithms
Active model-based segmentation has frequently been used in medical image processing with considerable success. Although the active model-based method was initially viewed as an op...
Yong Fan, Tianzi Jiang, David J. Evans
CVPR
2010
IEEE
13 years 10 months ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper
JMLR
2010
148views more  JMLR 2010»
13 years 1 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