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HIS
2003
13 years 10 months ago
A Hybrid Approach for Learning Parameters of Probabilistic Networks from Incomplete Databases
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...
S. Haider
CORR
2010
Springer
80views Education» more  CORR 2010»
13 years 8 months ago
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when ch...
Frederic Thouin, Mark Coates, Michael Rabbat
AI
1998
Springer
14 years 26 days ago
A Hybrid Convergent Method for Learning Probabilistic Networks
During past few years, a variety of methods have been developed for learning probabilistic networks from data, among which the heuristic single link forward or backward searches ar...
Jun Liu, Kuo-Chu Chang, Jing Zhou
ICCV
2005
IEEE
14 years 10 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICIP
2010
IEEE
13 years 6 months ago
Learning image similarities via Probabilistic Feature Matching
In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
Ziming Zhang, Ze-Nian Li, Mark S. Drew