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ICASSP
2011
IEEE
12 years 9 months ago
Belief theoretic methods for soft and hard data fusion
In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
CORR
2010
Springer
204views Education» more  CORR 2010»
13 years 4 months ago
Predictive State Temporal Difference Learning
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Byron Boots, Geoffrey J. Gordon
CVPR
2010
IEEE
13 years 8 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
BIOINFORMATICS
2005
93views more  BIOINFORMATICS 2005»
13 years 5 months ago
Donuts, scratches and blanks: robust model-based segmentation of microarray images
Inner holes, artifacts and blank spots are common in microarray images, but current image analysis methods do not pay them enough attention. We propose a new robust model-based me...
Qunhua Li, Chris Fraley, Roger Eugene Bumgarner, K...
ATAL
2005
Springer
13 years 11 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson