Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09
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TOTAL DOCUMENTS

180

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Published By ACM Press

9781605585161

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Optimized expected information gain for nonlinear dynamical systems

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553387 ◽

2009 ◽

Cited By ~ 9

Author(s):

Alberto Giovanni Busetto ◽

Cheng Soon Ong ◽

Joachim M. Buhmann

Keyword(s):

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Information Gain ◽

Nonlinear Dynamical ◽

Expected Information ◽

Expected Information Gain

Compositional noisy-logical learning

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553528 ◽

2009 ◽

Author(s):

Alan Yuille ◽

Songfeng Zheng

Learning linear dynamical systems without sequence information

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553430 ◽

2009 ◽

Author(s):

Tzu-Kuo Huang ◽

Jeff Schneider

Keyword(s):

Dynamical Systems ◽

Sequence Information ◽

Linear Dynamical Systems

Supervised learning from multiple experts

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553488 ◽

2009 ◽

Cited By ~ 142

Author(s):

Vikas C. Raykar ◽

Shipeng Yu ◽

Linda H. Zhao ◽

Anna Jerebko ◽

Charles Florin ◽

...

Keyword(s):

Supervised Learning ◽

Multiple Experts

Curriculum learning

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553380 ◽

2009 ◽

Cited By ~ 699

Author(s):

Yoshua Bengio ◽

Jérôme Louradour ◽

Ronan Collobert ◽

Jason Weston

Domain adaptation from multiple sources via auxiliary classifiers

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553411 ◽

2009 ◽

Cited By ~ 117

Author(s):

Lixin Duan ◽

Ivor W. Tsang ◽

Dong Xu ◽

Tat-Seng Chua

Keyword(s):

Domain Adaptation ◽

Multiple Sources

Good learners for evil teachers

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553404 ◽

2009 ◽

Cited By ~ 38

Author(s):

Ofer Dekel ◽

Ohad Shamir

Robust feature extraction via information theoretic learning

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553526 ◽

2009 ◽

Cited By ~ 78

Author(s):

Xiao-Tong Yuan ◽

Bao-Gang Hu

Keyword(s):

Feature Extraction ◽

Information Theoretic ◽

Information Theoretic Learning ◽

Robust Feature Extraction

Prototype vector machine for large scale semi-supervised learning

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553531 ◽

2009 ◽

Cited By ~ 50

Author(s):

Kai Zhang ◽

James T. Kwok ◽

Bahram Parvin

Keyword(s):

Supervised Learning ◽

Large Scale

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 ◽

10.1145/1553374.1553426 ◽

2009 ◽

Cited By ~ 32

Author(s):

Verena Heidrich-Meisner ◽

Christian Igel

Keyword(s):

Policy Search

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By ACM Press

Optimized expected information gain for nonlinear dynamical systems

Compositional noisy-logical learning

Learning linear dynamical systems without sequence information

Supervised learning from multiple experts

Curriculum learning

Domain adaptation from multiple sources via auxiliary classifiers

Good learners for evil teachers

Robust feature extraction via information theoretic learning

Prototype vector machine for large scale semi-supervised learning

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search

Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09
Latest Publications