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Conference Papers Year : 2010

Approximate nearest neighbors using sparse representations


A new method is introduced that makes use of sparse image representations to search for approximate nearest neighbors (ANN) under the normalized inner-product distance. The approach relies on the construction of a new sparse vector designed to approximate the normalized inner-product between underlying signal vectors. The resulting ANN search algorithm shows significant improvement compared to querying with the original sparse vectors. The system makes use of a proposed transform that succeeds in uniformly distributing the input dataset on the unit sphere while preserving relative angular distances.

Dates and versions

inria-00561778 , version 1 (01-02-2011)



Joaquin Zepeda, Ewa Kijak, Christine Guillemot. Approximate nearest neighbors using sparse representations. IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'10, IEEE, Mar 2010, Dallas, TX, United States. ⟨10.1109/ICASSP.2010.5496145⟩. ⟨inria-00561778⟩
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