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» Modeling Classification and Inference Learning
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JMLR
2010
172views more  JMLR 2010»
14 years 9 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
CVPR
2007
IEEE
16 years 4 months ago
Learning Visual Representations using Images with Captions
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
Ariadna Quattoni, Michael Collins, Trevor Darrell
ICML
2010
IEEE
15 years 3 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
ICML
2010
IEEE
15 years 3 months ago
A Conditional Random Field for Multiple-Instance Learning
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...
Thomas Deselaers, Vittorio Ferrari
116
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IJCINI
2007
125views more  IJCINI 2007»
15 years 2 months ago
A Unified Approach To Fractal Dimensions
The Cognitive Processes of Abstraction and Formal Inferences J. A. Anderson: A Brain-Like Computer for Cognitive Software Applications: the Resatz Brain Project L. Flax: Cognitive ...
Witold Kinsner