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» Arguing from Experience to Classifying Noisy Data
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JMLR
2010
136views more  JMLR 2010»
13 years 3 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
LREC
2008
143views Education» more  LREC 2008»
13 years 10 months ago
Building Affective Lexicons from Specific Corpora for Automatic Sentiment Analysis
Automatic sentiment analysis in texts has attracted considerable attention in recent years. Most of the approaches developed to classify texts or sentences as positive or negative...
Yves Bestgen
JMLR
2008
100views more  JMLR 2008»
13 years 9 months ago
Hit Miss Networks with Applications to Instance Selection
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Elena Marchiori
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 9 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
ICIP
2005
IEEE
14 years 10 months ago
No-reference video quality metric based on artifact measurements
In this paper we present a no-reference video quality metric based on individual measurements of three artifacts: blockiness, blurriness, and noisiness. The set of artifact metric...
Mylene Christine Queiroz de Farias, Sanjit K. Mitr...