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» Learning from Ambiguously Labeled Examples
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ICML
2007
IEEE
14 years 11 months ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
CVPR
2010
IEEE
14 years 7 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
DAGSTUHL
1994
14 years 10 days ago
Function-Based Object Recognition
Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally assoc...
Louise Stark, Kevin W. Bowyer
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
14 years 5 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan
CVPR
2009
IEEE
15 years 6 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...