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AMAI
2006
Springer
15 years 6 months ago
Symmetric approximate linear programming for factored MDPs with application to constrained problems
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
Dmitri A. Dolgov, Edmund H. Durfee
BMVC
2010
15 years 4 months ago
Learning Directional Local Pairwise Bases with Sparse Coding
Recently, sparse coding has been receiving much attention in object and scene recognition tasks because of its superiority in learning an effective codebook over k-means clusterin...
Nobuyuki Morioka, Shin'ichi Satoh
ACL
2009
15 years 4 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
ICCV
2011
IEEE
14 years 6 months ago
Sparse Dictionary-based Representation and Recognition of Action Attributes
We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective func...
Qiang Qiu, Zhuolin Jiang, Rama Chellappa
CVPR
2007
IEEE
16 years 28 days ago
A Graph Reduction Method for 2D Snake Problems
Energy-minimizing active contour models (snakes) have been proposed for solving many computer vision problems such as object segmentation, surface reconstruction, and object track...
Jianhua Yan, Keqi Zhang, Chengcui Zhang, Shu-Ching...