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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 2 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
CIKM
2009
Springer
15 years 9 months ago
Semi-supervised learning of semantic classes for query understanding: from the web and for the web
Understanding intents from search queries can improve a user’s search experience and boost a site’s advertising profits. Query tagging via statistical sequential labeling mode...
Ye-Yi Wang, Raphael Hoffmann, Xiao Li, Jakub Szyma...
ATAL
2003
Springer
15 years 7 months ago
Natural methods for robot task learning: instructive demonstrations, generalization and practice
Among humans, teaching various tasks is a complex process which relies on multiple means for interaction and learning, both on the part of the teacher and of the learner. Used tog...
Monica N. Nicolescu, Maja J. Mataric
ACCV
2010
Springer
14 years 9 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...
SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
13 years 4 months ago
Large-scale machine learning at twitter
The success of data-driven solutions to difficult problems, along with the dropping costs of storing and processing massive amounts of data, has led to growing interest in largesc...
Jimmy Lin, Alek Kolcz