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ICCV
2011
IEEE
12 years 7 months ago
iGroup : Weakly supervised image and video grouping
We present a generic, efficient and iterative algorithm for interactively clustering classes of images and videos. The approach moves away from the use of large hand labelled tra...
Andrew Gilbert, Richard Bowden
NIPS
2003
13 years 9 months ago
Log-Linear Models for Label Ranking
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
Ofer Dekel, Christopher D. Manning, Yoram Singer
DATAMINE
2010
161views more  DATAMINE 2010»
13 years 5 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
CIKM
2009
Springer
14 years 2 months ago
Combining labeled and unlabeled data with word-class distribution learning
We describe a novel simple and highly scalable semi-supervised method called Word-Class Distribution Learning (WCDL), and apply it the task of information extraction (IE) by utili...
Yanjun Qi, Ronan Collobert, Pavel Kuksa, Koray Kav...
ACL
2006
13 years 9 months ago
Boosting Statistical Word Alignment Using Labeled and Unlabeled Data
This paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. The proposed approach ...
Hua Wu, Haifeng Wang, Zhan-yi Liu