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NIPS
2007
13 years 10 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
CIKM
1995
Springer
14 years 10 days ago
Learning Subjective Relevance to Facilitate Information Access
As the amount of available electronic information is dramatically increasing, the ability for rapid and e ective access to information has become critical. Most traditional inform...
James R. Chen, Nathalie Mathe
IJON
2006
99views more  IJON 2006»
13 years 8 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
EMNLP
2007
13 years 10 months ago
Building Lexicon for Sentiment Analysis from Massive Collection of HTML Documents
Recognizing polarity requires a list of polar words and phrases. For the purpose of building such lexicon automatically, a lot of studies have investigated (semi-) unsupervised me...
Nobuhiro Kaji, Masaru Kitsuregawa
KES
2005
Springer
14 years 2 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh