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ICML
2003
IEEE
16 years 7 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
DAGM
2009
Springer
16 years 1 months ago
Learning with Few Examples by Transferring Feature Relevance
The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
Erik Rodner, Joachim Denzler
ICPR
2008
IEEE
16 years 8 months ago
On refining dissimilarity matrices for an improved NN learning
Application-specific dissimilarity functions can be used for learning from a set of objects represented by pairwise dissimilarity matrices in this context. These dissimilarities m...
Elzbieta Pekalska, Robert P. W. Duin
DBSEC
2010
319views Database» more  DBSEC 2010»
15 years 8 months ago
Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach
As online social networking sites become more and more popular, they have also attracted the attentions of the spammers. In this paper, Twitter, a popular micro-blogging service, i...
Alex Hai Wang
ICRA
2009
IEEE
227views Robotics» more  ICRA 2009»
16 years 1 months ago
Adaptive autonomous control using online value iteration with gaussian processes
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
Axel Rottmann, Wolfram Burgard