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» Active Learning for Class Probability Estimation and Ranking
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KDD
2012
ACM
212views Data Mining» more  KDD 2012»
11 years 9 months ago
Factoring past exposure in display advertising targeting
Online advertising is increasingly becoming more performance oriented, where the decision to show an advertisement to a user is made based on the user’s propensity to respond to...
Neha Gupta, Abhimanyu Das, Sandeep Pandey, Vijay K...
JMLR
2010
147views more  JMLR 2010»
13 years 1 months ago
Image Denoising with Kernels Based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian approaches working in wavelet representations. The performance of these methods improves when relations among th...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
BMCBI
2010
97views more  BMCBI 2010»
13 years 6 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 7 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
PRL
2007
138views more  PRL 2007»
13 years 6 months ago
Ent-Boost: Boosting using entropy measures for robust object detection
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
Duy-Dinh Le, Shin'ichi Satoh