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ICPR
2008
IEEE
15 years 4 months ago
Boosting Gaussian mixture models via discriminant analysis
The Gaussian mixture model (GMM) can approximate arbitrary probability distributions, which makes it a powerful tool for feature representation and classification. However, it su...
Hao Tang, Thomas S. Huang
NIPS
2008
14 years 11 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
IJON
2010
189views more  IJON 2010»
14 years 8 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin
MOBICOM
2004
ACM
15 years 3 months ago
Revisiting the TTL-based controlled flooding search: optimality and randomization
In this paper we consider the problem of searching for a node or an object (i.e., piece of data, file, etc.) in a large network. Applications of this problem include searching fo...
Nicholas B. Chang, Mingyan Liu
ICML
2009
IEEE
15 years 10 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel