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» Learning SVMs from Sloppily Labeled Data
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IS
2008
13 years 7 months ago
Mining relational data from text: From strictly supervised to weakly supervised learning
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Zhu Zhang
ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 6 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
ECIR
2007
Springer
13 years 9 months ago
Active Learning with History-Based Query Selection for Text Categorisation
Automated text categorisation systems learn a generalised hypothesis from large numbers of labelled examples. However, in many domains labelled data is scarce and expensive to obta...
Michael Davy, Saturnino Luz
IJON
2010
181views more  IJON 2010»
13 years 6 months ago
Active learning with extremely sparse labeled examples
An active learner usually assumes there are some labeled data available based on which a moderate classifier is learned and then examines unlabeled data to manually label the mos...
Shiliang Sun, David R. Hardoon
NIPS
2008
13 years 9 months ago
A "Shape Aware" Model for semi-supervised Learning of Objects and its Context
We present an approach that combines bag-of-words and spatial models to perform semantic and syntactic analysis for recognition of an object based on its internal appearance and i...
Abhinav Gupta, Jianbo Shi, Larry S. Davis