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Sparse Component Analysis: a New Tool for Data Mining

Georgiev, P. ; Pardalos, P. ; Theis, Fabian J. ; Cichocki, A. ; Bakardjian, H. Pardalos, P. ; Boginski, V. ; Vazacopoulos, A. , eds.


Abstract

In many practical problems for data mining the data X under consideration (given as (m × N)-matrix) is of the form X = AS, where the matrices A and S with dimensions m×n and n × N respectively (often called mixing matrix or dictionary and source matrix) are unknown (m ≤ n < N). We formulate conditions (SCA-conditions) under which we can recover A and S uniquely (up to scaling and permutation), ...

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