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ICML
2007
IEEE
14 years 9 months ago
Experimental perspectives on learning from imbalanced data
We present a comprehensive suite of experimentation on the subject of learning from imbalanced data. When classes are imbalanced, many learning algorithms can suffer from the pers...
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napol...
ISMDA
2001
Springer
14 years 1 months ago
Learning Bayesian-Network Topologies in Realistic Medical Domains
In recent years, a number of algorithms have been developed for learning the structure of Bayesian networks from data. In this paper we apply some of these algorithms to a realist...
Xiaofeng Wu, Peter J. F. Lucas, Susan Kerr, Roelf ...
GRC
2008
IEEE
13 years 9 months ago
Neighborhood Smoothing Embedding for Noisy Manifold Learning
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Guisheng Chen, Junsong Yin, Deyi Li
ICALT
2006
IEEE
14 years 2 months ago
LIMBS: Open Source, Open Standards, and Open Content To Foster Learning Resource Exchanges
LIMBS is an open source brokerage system developed in the framework of the CALIBRATE project. LIMBS relies on open standards and open contents to promote exchanges of learning res...
Jean-Noel Colin, David Massart
CVPR
2004
IEEE
14 years 10 months ago
Bayesian Assembly of 3D Axially Symmetric Shapes from Fragments
We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated...
Andrew R. Willis, David B. Cooper