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IPMU
2010
Springer
15 years 5 months ago
Approximation of Data by Decomposable Belief Models
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
Radim Jirousek
ICIP
2002
IEEE
16 years 8 months ago
Unsupervised detection of contours using a statistical model
In this paper, we describe an unsupervised segmentation method for contours which proves quite adapted for the images obtained by electronic acquisition. We present two statistica...
François Destrempes, Max Mignotte
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
16 years 1 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
186
Voted
GFKL
2007
Springer
184views Data Mining» more  GFKL 2007»
16 years 26 days ago
A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems
Abstract. Artificial systems with a high degree of autonomy require reliable semantic information about the context they operate in. State interpretation, however, is a difficult ...
Daniel Meyer-Delius, Christian Plagemann, Georg vo...
CHI
2009
ACM
15 years 7 months ago
A performance model of selection techniques for p300-based brain-computer interfaces
In this paper, we propose a model to predict the performance of selection techniques using Brain-Computer Interfaces based on P300 signals. This model is based on Markov theory an...
Jean-Baptiste Sauvan, Anatole Lécuyer, Fabi...