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LREC
2008
128views Education» more  LREC 2008»
15 years 4 months ago
Relation between Agreement Measures on Human Labeling and Machine Learning Performance: Results from an Art History Domain
We discuss factors that affect human agreement on a semantic labeling task in the art history domain, based on the results of four experiments where we varied the number of labels...
Rebecca J. Passonneau, Thomas Lippincott, Tae Yano...
ACL
2008
15 years 4 months ago
Unsupervised Learning of Acoustic Sub-word Units
Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
Balakrishnan Varadarajan, Sanjeev Khudanpur, Emman...
JMLR
2010
136views more  JMLR 2010»
14 years 9 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
ECML
2005
Springer
15 years 8 months ago
Learning from Positive and Unlabeled Examples with Different Data Distributions
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...
Xiaoli Li, Bing Liu
BMVC
2000
15 years 4 months ago
Object Recognition using the Invariant Pixel-Set Signature
A new object recognition method, the Invariant Pixel Set Signature (IPSS), is introduced. Objects are represented with a probability density on the space of invariants computed fr...
Jiri Matas, J. Burianek, Josef Kittler