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» Learning SVMs from Sloppily Labeled Data
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CVPR
2010
IEEE
14 years 5 months ago
Visual Event Recognition in Videos by Learning from Web Data
We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). First, we propose a new...
Lixin Duan, Dong Xu, Wai-Hung Tsang, Jiebo Luo
EMNLP
2004
13 years 10 months ago
Active Learning and the Total Cost of Annotation
Active learning (AL) promises to reduce the cost of annotating labeled datasets for trainable human language technologies. Contrary to expectations, when creating labeled training...
Jason Baldridge, Miles Osborne
ECML
2007
Springer
14 years 3 months ago
Discriminative Sequence Labeling by Z-Score Optimization
Abstract. We consider a new discriminative learning approach to sequence labeling based on the statistical concept of the Z-score. Given a training set of pairs of hidden-observed ...
Elisa Ricci, Tijl De Bie, Nello Cristianini
CVPR
2004
IEEE
14 years 11 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
LREC
2008
103views Education» more  LREC 2008»
13 years 10 months ago
From Field Notes towards a Knowledge Base
We describe the process of converting plain text cultural heritage data to elements of a domain-specific knowledge base, using general machine learning techniques. First, digitise...
Piroska Lendvai, Steve Hunt