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Fast greedy algorithms for dictionary selection with generalized sparsity constraints
Kaito Fujii · Tasuku Soma

Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #78

In dictionary selection, several atoms are selected from finite candidates that successfully approximate given data points in the sparse representation. We propose a novel efficient greedy algorithm for dictionary selection. Not only does our algorithm work much faster than the known methods, but it can also handle more complex sparsity constraints, such as average sparsity. Using numerical experiments, we show that our algorithm outperforms the known methods for dictionary selection, achieving competitive performances with dictionary learning algorithms in a smaller running time.

Author Information

Kaito Fujii (University of Tokyo)
Tasuku Soma (University of Tokyo)

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