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» Unifying generative and discriminative learning principles
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PKDD
2015
Springer
23views Data Mining» more  PKDD 2015»
3 years 7 months ago
Online Learning of Deep Hybrid Architectures for Semi-supervised Categorization
A hybrid architecture is presented capable of online learning from both labeled and unlabeled samples. It combines both generative and discriminative objectives to derive a new var...
Alexander G. Ororbia II, David Reitter, Jian Wu, C...
WSOM
2009
Springer
9 years 6 months ago
Bag-of-Features Codebook Generation by Self-Organisation
Bag of features is a well established technique for the visual categorisation of objects, categories of objects and textures. One of the most important part of this technique is co...
Teemu Kinnunen, Joni-Kristian Kämärä...
IJCV
2006
161views more  IJCV 2006»
8 years 12 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
AAAI
2000
9 years 1 months ago
Restricted Bayes Optimal Classifiers
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Simon Tong, Daphne Koller
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
8 years 10 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...
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