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TSMC
2011
210views more  TSMC 2011»
14 years 10 months ago
Fault Diagnosis in Discrete-Event Systems: Incomplete Models and Learning
— Most state-based approaches to fault diagnosis of discrete-event systems require a complete and accurate model of the system to be diagnosed. In this paper, we address the prob...
Raymond H. Kwong, David L. Yonge-Mallo
JMLR
2010
125views more  JMLR 2010»
14 years 10 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
ICASSP
2011
IEEE
14 years 7 months ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro
CORR
2012
Springer
185views Education» more  CORR 2012»
13 years 11 months ago
Bayesian network learning with cutting planes
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
James Cussens
131
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ICIP
2006
IEEE
16 years 4 months ago
Knowledge-Based Supervised Learning Methods in a Classical Problem of Video Object Tracking
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...