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» Associativity between feature models across domains
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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 8 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ICCV
2001
IEEE
14 years 9 months ago
Learning the Semantics of Words and Pictures
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features...
Kobus Barnard, David A. Forsyth
SIAMIS
2010
176views more  SIAMIS 2010»
13 years 6 months ago
Optimized Conformal Surface Registration with Shape-based Landmark Matching
Surface registration, which transforms different sets of surface data into one common reference space, is an important process which allows us to compare or integrate the surface ...
Lok Ming Lui, Sheshadri R. Thiruvenkadam, Yalin Wa...
CVPR
2011
IEEE
13 years 3 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
SAC
2010
ACM
13 years 2 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane