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NECO
2007
129views more  NECO 2007»
15 years 6 months ago
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Shinichi Nakajima, Sumio Watanabe
221
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CORR
2010
Springer
204views Education» more  CORR 2010»
15 years 5 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
CORR
2011
Springer
220views Education» more  CORR 2011»
15 years 1 months ago
On a linear programming approach to the discrete Willmore boundary value problem and generalizations
We consider the problem of finding (possibly non connected) discrete surfaces spanning a finite set of discrete boundary curves in the three-dimensional space and minimizing (glo...
Thomas Schoenemann, Simon Masnou, Daniel Cremers
SIAMIS
2011
15 years 1 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
CVPR
2007
IEEE
16 years 8 months ago
Graph Cut Based Optimization for MRFs with Truncated Convex Priors
Optimization with graph cuts became very popular in recent years. Progress in problems such as stereo correspondence, image segmentation, etc., can be attributed, in part, to the ...
Olga Veksler