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» Modeling Classification and Inference Learning
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CVPR
2008
IEEE
14 years 10 months ago
Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision
Many applications in computer vision and pattern recognition involve drawing inferences on certain manifoldvalued parameters. In order to develop accurate inference algorithms on ...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap...
ICIP
2006
IEEE
14 years 9 months ago
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
AGENTS
1999
Springer
14 years 4 days ago
Learning to Remove Internet Advertisements
This paper discusses improving the methodology introduced in Kushmerick’s paper about learning to remove internet advertisements. The aim is to reduce the model build time as we...
Nicholas Kushmerick
CVIU
2004
132views more  CVIU 2004»
13 years 7 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Nuria Oliver, Ashutosh Garg, Eric Horvitz
BMCBI
2010
143views more  BMCBI 2010»
13 years 8 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli