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JAIR
1998
198views more  JAIR 1998»
15 years 2 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
CVPR
2011
IEEE
14 years 6 months ago
How does Person Identity Recognition Help Multi-Person Tracking?
We address the problem of multi-person tracking in a complex scene from a single camera. Although trackletassociation methods have shown impressive results in several challenging ...
Cheng-Hao Kuo, Ram Nevatia
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 9 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
SDM
2009
SIAM
394views Data Mining» more  SDM 2009»
16 years 9 days ago
Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
Oksana Yakhnenko, Vasant Honavar
AUSAI
2008
Springer
15 years 5 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe