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PERCOM
2007
ACM
14 years 8 months ago
Sensor Scheduling for Optimal Observability Using Estimation Entropy
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Mohammad Rezaeian
PAKDD
2009
ACM
171views Data Mining» more  PAKDD 2009»
14 years 1 months ago
Detecting Abnormal Events via Hierarchical Dirichlet Processes
Abstract. Detecting abnormal event from video sequences is an important problem in computer vision and pattern recognition and a large number of algorithms have been devised to tac...
Xian-Xing Zhang, Hua Liu, Yang Gao, Derek Hao Hu
IJFCS
2008
49views more  IJFCS 2008»
13 years 8 months ago
A Markovian Approach for the Analysis of the gene Structure
Hidden Markov models (HMMs) are effective tools to detect series of statistically homogeneous structures, but they are not well suited to analyse complex structures. Numerous meth...
Christelle Melo de Lima, Laurent Gueguen, Christia...
INCDM
2010
Springer
204views Data Mining» more  INCDM 2010»
14 years 4 days ago
Combining Business Process and Data Discovery Techniques for Analyzing and Improving Integrated Care Pathways
Hospitals increasingly use process models for structuring their care processes. Activities performed to patients are logged to a database but these data are rarely used for managin...
Jonas Poelmans, Guido Dedene, Gerda Verheyden, Her...
ICASSP
2010
IEEE
13 years 9 months ago
Phone recognition using Restricted Boltzmann Machines
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
Abdel-rahman Mohamed, Geoffrey E. Hinton