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» On the Convergence of Boosting Procedures
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ICPR
2008
IEEE
14 years 10 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
MICCAI
2003
Springer
14 years 9 months ago
Topological Correction of Subcortical Segmentation
Abstract. We propose a method for automatically correcting the spherical topology of any segmentation under any digital connectivity. A multiple region growing process, concurrentl...
Florent Ségonne, W. Eric L. Grimson, Bruce ...
ICML
2000
IEEE
14 years 9 months ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
ICML
1998
IEEE
14 years 9 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
ICPR
2008
IEEE
14 years 3 months ago
Matching images more efficiently with local descriptors
Image matching is a fundamental task for many applications of computer vision. Today it is very popular to represent two matched images as two bags of local descriptors, and the c...
Dong Zhang, Weiqiang Wang, Qingming Huang, Shuqian...