Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences
نویسندگان
چکیده
منابع مشابه
Riemannian Sparse Coding for Positive Definite Matrices
Inspired by the great success of sparse coding for vector valued data, our goal is to represent symmetric positive definite (SPD) data matrices as sparse linear combinations of atoms from a dictionary, where each atom itself is an SPD matrix. Since SPD matrices follow a non-Euclidean (in fact a Riemannian) geometry, existing sparse coding techniques for Euclidean data cannot be directly extende...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks and Learning Systems
سال: 2016
ISSN: 2162-237X,2162-2388
DOI: 10.1109/tnnls.2014.2387383