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CVPR
1997
IEEE
15 years 12 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun
ESCAPE
2007
Springer
256views Algorithms» more  ESCAPE 2007»
15 years 1 months ago
A More Effective Linear Kernelization for Cluster Editing
In the NP-hard Cluster Editing problem, we have as input an undirected graph G and an integer k 0. The question is whether we can transform G, by inserting and deleting at most k ...
Jiong Guo
ICML
2010
IEEE
14 years 11 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
ICML
2005
IEEE
15 years 10 months ago
Linear Asymmetric Classifier for cascade detectors
The detection of faces in images is fundamentally a rare event detection problem. Cascade classifiers provide an efficient computational solution, by leveraging the asymmetry in t...
Jianxin Wu, Matthew D. Mullin, James M. Rehg
ICASSP
2009
IEEE
15 years 4 months ago
Adaptive distributed transforms for irregularly sampled Wireless Sensor Networks
We develop energy-efficient, adaptive distributed transforms for data gathering in wireless sensor networks. In particular, we consider a class of unidirectional transforms that ...
Godwin Shen, Sunil K. Narang, Antonio Ortega