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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...
PAKDD
2011
ACM
473views Data Mining» more  PAKDD 2011»
15 years 12 days ago
 Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy Hospedales, Shaogang Gong and Tao Xiang
CSCWD
2007
Springer
16 years 27 days ago
Digital Identity Design and Privacy Preservation for e-Learning
More and more learners tend to utilise e-learning as their learning platform. The privacy of the users’ digital identities of e-learning has become a big concern. This paper pro...
Jianming Yong
145
Voted
ANLP
1997
86views more  ANLP 1997»
15 years 8 months ago
Nymble: a High-Performance Learning Name-finder
This paper presents a statistical, learned approach to finding names and other nonrecursive entities in text (as per the MUC-6 definition of the NE task), using a variant of the s...
Daniel M. Bikel, Scott Miller, Richard M. Schwartz...
CORR
2011
Springer
161views Education» more  CORR 2011»
14 years 10 months ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li