GitHub - samehkhamis/FaceSDPAD: Face recognition using a Probabilistic Semidefinite Model trained using an Alternating Direction Augmented Lagrangian method

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Face recognition using a Probabilistic Semidefinite Model trained using an Alternating Direction Augmented Lagrangian method

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Name		Name	Last commit message	Last commit date
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FaceDataset.m		FaceDataset.m
PCA.m		PCA.m
README		README
SDPAD.m		SDPAD.m
SPM.m		SPM.m
att.mat		att.mat
run_libsvm.m		run_libsvm.m
run_sdpad.m		run_sdpad.m
run_sedumi.m		run_sedumi.m
yale.mat		yale.mat

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Class Project: Alternating Direction Augmented Lagrangian for Probabilistic Semidefinite Models
Date: Dec 2010
Based on:
1. Crammer and Globerson. Discriminative learning via probabilistic semidefinite models. In: UAI, 2006.
2. Wen, Goldfarb, and Yin. Alternating Direction Augmented Lagrangian Methods for Semidefinite Programming. Mathematical Programming Computation, 2009.

The code implements the alternating direction methods in [2] to solve a 2-class version of the model in [1].
Code is online mainly for my reference. It is licensed under GPLv2 for non-commercial research purposes only.
The experiments were run on the Yale and AT&T faces datasets.