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» A New Discriminative Kernel From Probabilistic Models
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ICCV
1999
IEEE
15 years 4 months ago
Learning Low-Level Vision
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...
William T. Freeman, Egon C. Pasztor
CVPR
2005
IEEE
16 years 1 months ago
Graph Embedding: A General Framework for Dimensionality Reduction
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
Shuicheng Yan, Dong Xu, Benyu Zhang, HongJiang Zha...
ISCI
2008
181views more  ISCI 2008»
14 years 12 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
ACL
1996
15 years 1 months ago
Minimizing Manual Annotation Cost in Supervised Training from Corpora
Corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. This paper investigates methods for ...
Sean P. Engelson, Ido Dagan
NIPS
2001
15 years 1 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona