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CORR
2010
Springer

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition

9 years 7 days ago
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of these bases. The applicability of these methods to visual object recognition tasks has been limited because of the prohibitive cost of the optimization algorithms required to compute the sparse representation. In this work we propose a simple and efficient algorithm to learn basis functions. After training, this model also provides a fast and smooth approximator to the optimal representation, achieving even better accuracy than exact sparse coding algorithms on visual object recognition tasks.
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCu
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun
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