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ECCV
2006
Springer
16 years 5 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
117
Voted
CORR
2010
Springer
96views Education» more  CORR 2010»
15 years 3 months ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
151
Voted
ICCV
2003
IEEE
16 years 5 months ago
Unified Subspace Analysis for Face Recognition
We propose a face difference model that decomposes face difference into three components, intrinsic difference, transformation difference, and noise. Using the face difference mod...
Xiaogang Wang, Xiaoou Tang
ICIP
2008
IEEE
16 years 5 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
135
Voted
DAGM
2006
Springer
15 years 7 months ago
Probabilistic De Novo Peptide Sequencing with Doubly Charged Ions
Sequencing of peptides by tandem mass spectrometry has matured to the key technology for proteomics. Noise in the measurement process strongly favors statistical models like NovoHM...
Hansruedi Peter, Bernd Fischer, Joachim M. Buhmann