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» An improvement on learning with local and global consistency
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FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
14 years 2 months ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
ECCV
2010
Springer
14 years 1 months ago
Learning What and How of Contextual Models for Scene Labeling
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
ICCBR
1997
Springer
14 years 1 days ago
Examining Locally Varying Weights for Nearest Neighbor Algorithms
Previous work on feature weighting for case-based learning algorithms has tended to use either global weights or weights that vary over extremely local regions of the case space. T...
Nicholas Howe, Claire Cardie
ICML
2008
IEEE
14 years 8 months ago
Estimating local optimums in EM algorithm over Gaussian mixture model
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung