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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ECTEL
2006
Springer
15 years 10 months ago
A Formal Model of Learning Object Metadata
In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is t...
Kris Cardinaels, Erik Duval, Henk J. Olivié
ESANN
2008
15 years 8 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
IJCAI
1997
15 years 7 months ago
Is Nonparametric Learning Practical in Very High Dimensional Spaces?
Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
Gregory Z. Grudic, Peter D. Lawrence
CVPR
2003
IEEE
16 years 8 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai