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» Learning from Ambiguously Labeled Images
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KDD
2010
ACM
286views Data Mining» more  KDD 2010»
13 years 6 months ago
Nonnegative shared subspace learning and its application to social media retrieval
Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can ser...
Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Tru...
NIPS
2003
13 years 9 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 11 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
CVPR
2012
IEEE
11 years 11 months ago
Leveraging category-level labels for instance-level image retrieval
In this article, we focus on the problem of large-scale instance-level image retrieval. For efficiency reasons, it is common to represent an image by a fixed-length descriptor w...
Albert Gordo, José A. Rodríguez-Serr...
DSMML
2004
Springer
14 years 1 months ago
Object Recognition via Local Patch Labelling
Abstract. In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of...
Christopher M. Bishop, Ilkay Ulusoy