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» Variations on U-Shaped Learning
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MLDM
2010
Springer
14 years 7 months ago
The Impact of Experimental Setup in Prepaid Churn Prediction for Mobile Telecommunications: What to Predict, for Whom and Does t
Prepaid customers in mobile telecommunications are not bound by a contract and can therefore change operators (`churn') at their convenience and without notification. This mak...
Dejan Radosavljevik, Peter van der Putten, Kim Kyl...
CVPR
2010
IEEE
15 years 8 months ago
Spatialized Epitome and Its Applications
Due to the lack of explicit spatial consideration, existing epitome model may fail for image recognition and target detection, which directly motivates us to propose the so-calle...
Xinqi Chu, Shuicheng Yan, Liyuan Li, Kap Luk Chan,...
ICCV
2011
IEEE
14 years 22 days ago
Building a better probabilistic model of images by factorization
We describe a directed bilinear model that learns higherorder groupings among features of natural images. The model represents images in terms of two sets of latent variables: one...
Jack Culpepper, Jascha Sohl-Dickstein, Bruno Olaha...
139
Voted
ICDAR
2011
IEEE
14 years 10 days ago
Co-training for Handwritten Word Recognition
—To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on...
Volkmar Frinken, Andreas Fischer, Horst Bunke, Ali...
110
Voted
TNN
2008
178views more  TNN 2008»
15 years 18 days ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen