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CVPR
2009
IEEE
15 years 2 months ago
Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer
We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
14 years 7 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 7 months ago
Active Learning for Hidden Attributes in Networks
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
Xiaoran Yan, Yaojia Zhu, Jean-Baptiste Rouquier, C...
ICML
2010
IEEE
13 years 8 months ago
Efficient Learning with Partially Observed Attributes
We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the ca...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
ACL
2010
13 years 5 months ago
Hierarchical Sequential Learning for Extracting Opinions and Their Attributes
Automatic opinion recognition involves a number of related tasks, such as identifying the boundaries of opinion expression, determining their polarity, and determining their inten...
Yejin Choi, Claire Cardie