Binary adaptive embeddings from order statistics of random projections

Diego Valsesia, Enrico Magli

IEEE Signal Processing Letters, vol. 24, no. 1, pp. 111-115, Jan. 2017

Abstract

We use some of the largest order statistics of the random projections of a reference signal to construct a binary embedding that is adapted to signals correlated with such signal. The embedding is characterized from the analytical standpoint and shown to provide improved performance on tasks such as classification in a reduced-dimensionality space.

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