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» Imitation Learning Using Graphical Models
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ACL
1998
13 years 9 months ago
Learning Intonation Rules for Concept to Speech Generation
In this paper, we report on an effort to provide a general-purpose spoken language generation tool for Concept-to-Speech (CTS) applications by extending a widely used text generat...
Shimei Pan, Kathleen McKeown
JMLR
2010
179views more  JMLR 2010»
13 years 3 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
ICML
2005
IEEE
14 years 9 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
UAI
2003
13 years 9 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
RSEISP
2007
Springer
14 years 2 months ago
Generalizing Data in Natural Language
This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computergenerated knowledge not only to have high predicti...
Ryszard S. Michalski, Janusz Wojtusiak