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» Causal inference using the algorithmic Markov condition
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SCVMA
2004
Springer
15 years 10 months ago
Motion Detection Using Wavelet Analysis and Hierarchical Markov Models
This paper deals with the motion detection problem. This issue is of key importance in many application fields. To solve this problem, we compute the dominant motion in the sequen...
Cédric Demonceaux, Djemâa Kachi-Akkou...
142
Voted
NIPS
2004
15 years 6 months ago
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...
182
Voted
ICIP
1998
IEEE
16 years 6 months ago
Adaptive Restoration of Speckled SAR Images using a Compound Random Markov Field
This paper proposes a restoration scheme for noisy images generated by coherent imaging systems (e.g., synthetic aperture radar, synthetic aperture sonar, ultrasound imaging, and ...
José M. B. Dias, José M. N. Leit&ati...
152
Voted
UAI
2008
15 years 6 months ago
Discovering Cyclic Causal Models by Independent Components Analysis
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
139
Voted
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 4 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang