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» Computational Techniques for Modelling Learning in Economics
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NECO
2002
104views more  NECO 2002»
14 years 9 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
ACL
2010
14 years 7 months ago
Distributional Similarity vs. PU Learning for Entity Set Expansion
Distributional similarity is a classic technique for entity set expansion, where the system is given a set of seed entities of a particular class, and is asked to expand the set u...
Xiaoli Li, Lei Zhang, Bing Liu, See-Kiong Ng
ICPR
2008
IEEE
15 years 4 months ago
Fast multiple instance learning via L1, 2 logistic regression
In this paper, we develop an efficient logistic regression model for multiple instance learning that combines L1 and L2 regularisation techniques. An L1 regularised logistic regr...
Zhouyu Fu, Antonio Robles-Kelly
107
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FGR
2004
IEEE
230views Biometrics» more  FGR 2004»
15 years 1 months ago
Tracking Humans using Prior and Learned Representations of Shape and Appearance
Tracking a moving person is challenging because a person's appearance in images changes significantly due to articulation, viewpoint changes, and lighting variation across a ...
Jongwoo Lim, David J. Kriegman
CCS
2006
ACM
15 years 1 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...