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ECML
2005
Springer
14 years 3 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
ACL
1998
13 years 11 months ago
Dialogue Act Tagging with Transformation-Based Learning
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract valu...
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
JMLR
2010
172views more  JMLR 2010»
13 years 4 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
14 years 4 months ago
Learning sound location from a single microphone
Abstract— We consider the problem of estimating the incident angle of a sound, using only a single microphone. The ability to perform monaural (single-ear) localization is import...
Ashutosh Saxena, Andrew Y. Ng
SIGIR
2005
ACM
14 years 3 months ago
Predicting query difficulty on the web by learning visual clues
We describe a method for predicting query difficulty in a precision-oriented web search task. Our approach uses visual features from retrieved surrogate document representations (...
Eric C. Jensen, Steven M. Beitzel, David A. Grossm...