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TSMC
2011
210views more  TSMC 2011»
13 years 5 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»
13 years 5 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
13 years 2 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»
12 years 6 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
ICIP
2006
IEEE
15 years 9 days 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...